The Colors of Investors’ Money: Which Firms AttractInstitutional Investors From Around the World?∗

Miguel A. Ferreira†

ISCTE Business School-LisbonCEMAF

Pedro P. Matos‡

Marshall School of BusinessUniversity of Southern California

This Version: April 2006

Abstract

We study institutional investors’ stock holdings around the world using a com-prehensive data set from 27 countries. Three groups of institutions based on theirgeographic origin (U.S., non-U.S. foreign, and domestic managers) have equal impor-tance in the shareholder base of non-U.S. corporations. Thus, we offer a global (non-U.S. centric) view on what firm- and country-level characteristics attract investmentby institutional investors. We find that all institutions reveal a strong preference forlarge and liquid stocks with good governance practices. There is, however, substantialdiversity between domestic and foreign institutions with respect to other firm charac-teristics. Foreign investors overweight stocks that are cross-listed in the U.S., membersof the MSCI indexes, and globally visible through high foreign sales or analyst coverage.Domestic institutions, in contrast, seem to underweight these same stocks. The cross-listing effect is not concentrated in the holdings of ADRs as a significant increase in theholdings of local shares by foreigners is found, which sheds some light on “multi-markettrading” and the ”flow-back” phenomena. Our findings show an important character-istic of modern international capital markets as firm and investor actions take place ininter-connected markets. Finally, we find that foreign institutional ownership has realeffects as it is positively associated with higher firm valuation.

JEL classification: G15, G20, G32Keywords: Institutional Investors, Cross-listing, International Capital Markets

∗We thank Paul Bennett, Luc Laeven, Andrew Karolyi, Michael Schill, Francis Warnock, and participantsat the University of Southern California Seminar and the Darden/World Bank 5th Annual Conference onEmerging Markets for helpful comments. This research is supported by FCT/POCI 2010.

†Address: Complexo INDEG/ISCTE, Av. Prof. Anibal Bettencourt, 1600-189 Lisboa, Portugal. Phone:+351.21.795.8607. Fax: +351.21.795.8605. Email: miguel.ferreira@iscte.pt.

‡Address: Hoffman Hall-701, MC-1427, 701 Exposition Blvd., Ste. 701, Los Angeles, CA 90089-1427,USA. Phone: 213.740.6533. Fax: 213-740-6650. Email: pmatos@marshall.usc.edu.

1. Introduction

A key element in modern capital markets is the interplay between firms that increasingly

raise capital internationally, and institutional investors that manage growing pools of assets.

Many individual investors around the world are selecting mutual funds, pension funds, or

retirement products offered by insurance companies and banks, as their main investment

vehicle. Institutional investors manage over US$ 9 trillion of equity assets in developed

markets, which represents a substantial share of these countries’ retirement savings and other

wealth (Organization for Economic Co-operation and Development (OECD (2003)).1 The

importance of institutional investors is also rapidly increasing in emerging market countries

(see, for example, International Monetary Fund (2004), and Khorana, Servaes, and Tufano

(2005)). These professional money managers have become major players in their domestic

stock markets, and they are more likely to invest abroad than individual investors. Most

publicly-traded corporations in many countries have now institutional investors as their

largest (minority) shareholders. These institutional investors, based on their geographic

origin, could be a U.S.-based mutual fund manager, a domestic pension fund, or a global

professional money manager.

This paper uses a novel database on institutional equity holdings around the world. We

offer a global (non-US centric) view of what attracts institutional investors to invest in cor-

porations worldwide. The data set contains stock-level holdings from over 3,000 institutions

from 27 countries, with positions totaling US$ 6.8 trillion as of December 2004, of which

US$ 2.7 trillion in over 18,000 non-U.S. stocks (the focus of our paper). US$ 1.8 trillion

of these holdings in non-U.S. stocks are cross-border investments. U.S.-based institutions

hold, on aggregate, over US$ 0.9 trillion overseas in non-U.S. stocks. This is matched by

non-U.S. institutional investors that hold US$ 0.9 trillion overseas in non-U.S. stocks, and

domestic institutions that hold an additional US$ 0.8 trillion in domestic stocks. Thus, while1Overall, institutional investors manage over US$ 35 trillion in OECD countries in equities, bonds, and

money market instruments.

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the majority of previous research looks at U.S. investors as the primary source of capital,

corporations worldwide are finding that three pools of professional investors (U.S., non-U.S.,

and domestic institutions) have similar pocket sizes.

We study the revealed stock preferences of these three different institutional investor

clienteles, and investigate what firm- and country-level characteristics attract these investors.

First, we find that all institutional investors, irrespective of their geographic origin, share

a preference for large, liquid, and widely-held stocks (i.e., without large controlling block-

holders).Second, all institutions reveal a preference for stocks of countries with strong disclo-

sure standards and geographically close to their home market. Third, foreign institutional

investors have a strong bias for firms that are members of the Morgan Stanley Capital In-

ternational (MSCI) All Country World Index and that are cross-listed in an U.S. exchange

by the way of an American Depositary Receipt (ADR). Domestic institutions, in contrast,

underweight these same stocks. Foreign and domestic institutional investors display other di-

vergences in their stock preferences. Foreign institutions tend to avoid high dividend-paying

firms, while these same firms are favored by domestic institutions. Foreign asset managers

exhibit high demand for firms with “name value” and foreign visibility (i.e., high foreign sales

and analyst coverage). Finally, U.S. and non-U.S. foreign investors disagree on holding value

versus growth stocks and on what are their favorite target markets. U.S. institutions show a

clear preference for English-speaking countries and less developed markets when they decide

to go abroad, while non-U.S. institutions hold relatively more stocks in non-English-speaking

countries and more developed markets. We conduct several robustness checks on these find-

ings and examine in more detail stock preferences by investors from different geographical

regions.

Overall, there are both similarities and diversity in the revealed stock preferences of the

various groups of institutional investors based on their geographic origin. Thus we conclude

that the "colors" (i.e. origin) of investors’ money matters. The analysis is conducted on

a sample of worldwide institutional investors’ individual stock holdings over the 2000-2004

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period. Thus, our findings are not hampered by studying: foreign ownership in firms from

a single origin country (Japan as in Kang and Stulz (1997) or Sweden as in Dahlquist and

Robertsson (2001)); foreign ownership by investors from a single country of origin (U.S. in-

vestors as in Aggarwal, Klapper, andWysocki (2005), Ammer, Holland, Smith, andWarnock

(2005), and Leuz, Lins, andWarnock (2005)); institutional holdings using country-level port-

folio allocations (Chan, Covrig, and Ng (2005)); institutional holdings from just one class of

institutions (mutual funds as in Chan et al. (2005) and Covrig, Lau, and Ng (2005)); insti-

tutional holdings using a single year of observations (as in Ammer et al. (2005), Chan et al.

(2005), and Covrig et al. (2005)). In addition, our data set also contains U.S. stock holdings,

which allows us to investigate U.S. institutions behavior at home, and match many of the

stylized facts documented in Gompers and Metrick (2001) in their study of U.S. domestic

institutional holdings.

We then investigate whether corporations can attract foreign capital more effectively by

cross-listing their shares in major financial centers in which institutional investors operate.

One of the most prominent mechanisms in recent years has been to list shares in the U.S.

market by way of an ADR program. The argument is that the firm can tap into the pool

of assets managed by U.S. investors who do not venture abroad because of transaction costs

or unfamiliar practices, or even into the pool of assets managed by non-U.S. investors who

prefer to trade in the U.S. market. The shares of cross-listed firms can potentially become

more liquid and the firm can have access to additional external funds at a lower cost. A

countervailing argument, however, is that there may be very few U.S. institutional investors

who cannot invest directly overseas (Financial Times (2004)). We test whether there is

indeed a cross-listing effect, i.e., whether a firm is able to expand its foreign shareholder

base when it cross-lists in an U.S. exchange. We find evidence of a significant increase in

U.S. institutional holdings when a firm launches an ADR program. Moreover, firms are also

able to capture a higher fraction of non-U.S. foreign institutional investors. In total, foreign

investors hold 5% more of the market capitalization of cross-listed firms than they would

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hold otherwise. We take into account the potential selection bias as firms that decide to

cross-list can be the type of firms that foreign investors would tend to hold regardless of the

cross-listing.

To further tackle this endogeneity issue, we isolate the 101 firms that launched an ADR

during our sample period (2000-2004). We find evidence that these firms experience an

increase in their shareholder base around the time of the cross-listing in the U.S. Although

foreign investors already have holdings in local shares of those firms prior to the ADR, they

substantially increase their position at the time of the cross-listing. Interestingly, however,

the increase mainly accrues in local shares holdings rather than in ADR shares holdings

directly. This finding sheds light on the ADRs “flow-back” phenomenon, i.e., after an initial

blip in U.S. trading of ADR shares, trading moves back to the more liquid domestic exchange

(Karolyi (2003) and Halling, Pagano, Randl, and Zechner (2004)). Even though trading is

not retained by the U.S. exchanges, cross-listed firms attract extra foreign investors on board

(both U.S. and non-U.S.) who are making the trip to the firm’s home market and invest in

local shares. Firm and investor actions occur in multiple but connected markets. This speaks

to the issues of “multi-market trading” (Baruch, Karolyi, and Lemmon (2005) and Karolyi

(2006)) and the distribution of the trading activity of cross-listed stocks between domestic

and international markets (Levine and Schmukler (2006)).

In a concluding analysis, we investigate whether the presence of foreign and domestic

institutional ownership drives up a firm’s valuation. Following the related literature (see,

for example, Lins (2003), Doidge, Karolyi, and Stulz (2004), and Durnev and Kim (2005)),

we regress a firm’s Tobin’s Q ratio on firm-level, industry-level, and country-level variables,

including the fraction of shares held by foreign and domestic institutional investors as a

potential determinant of firm valuation. We find that foreign institutional ownership has a

significant positive impact on firm valuation, unlike domestic institutional ownership. Be-

cause institutional ownership is likely to be jointly determined with firm’s Tobin’s Q ratio

and driven by other firm characteristics, we re-estimate the Tobin’s Q and institutional own-

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ership equations as a system of simultaneous equations. We find that the effect prevails and

accordingly there exists a strong positive relation between institutional foreign ownership

and firm valuation.

Our empirical results provide evidence of the real effects of a firm’s shareholder base in an

international capital markets setting. Our findings are consistent with market segmentation

theories (Merton (1987)) that firms held by a larger investor base have lower expected returns

demanded on their stocks. Other papers have analyzed how a firm’s decision to cross-list their

shares reduces a firm’s cost of capital (Foerster and Karolyi (1999) and Doidge et al. (2004)).

Our results, however, go one step further and offer a direct link between foreign (institutional)

shareholder presence and firms’ valuations. Our findings support the idea that the expansion

of the foreign institutional ownership base is one of the channels by which cross-listing in

the U.S. market reduces firms’ cost of capital. An alternative interpretation of our findings,

however, is that firms that attract foreign investors can become overvalued. The rise in firm

valuations can also be evidence of price pressure effects when a foreign investor clientele

buys into a stock. It is empirically difficult to distinguish between these two interpretations.

Recent literature on cross-listing argues that firm valuation benefits of internationalization

are transitory and dynamic (Levine and Schmukler (2005) and Sarkissian and Schill (2005)).

The results here also give additional insights to the issue of whether country-level gov-

ernance and firm-level governance are substitute or complementary mechanisms. Recent

research (Doidge, Karolyi, and Stulz (2005) and Stulz (2005)) finds evidence that firm-level

governance levels are in large part driven by country characteristics. We find, however, that

foreign and domestic investors decisions are largely driven by firm characteristics (and more

so, than by country characteristics). Our results indicate that investors engage in stock-level

analysis, and they dedicate particular attention to several firm-level governance indicators.

In addition, we find that institutions are more sensitive to firm-level governance mechanisms

in countries with weak country-level investor protection and quality of institutions. These

findings support a substitute role between firm-level and country-level mechanisms, rather

5

than a complementary role. Thus, investors track firm-level governance indicators (besides

country-level governance), and there is ”hope” for a ”good” firm in a ”bad” country.

The remainder the paper is organized as follows. Section 2 presents the institutional hold-

ings data, the sample of firms, and the determinants of institutional ownership. In section 3,

we conduct our tests on what firm and country characteristics attract institutional investors.

We also present a detailed investigation of the cross-listing effect on institutional ownership,

in particular foreign ownership. In section 4, we study the valuation effects of foreign and

domestic institutional ownership. Section 5 concludes and discusses the implications of our

work.

2. Data Description

2.1. Institutional Investors Holdings Data

The institutional investor holdings data are drawn from the FactSet/LionShares owner-

ship database, which is the leading information source for global institutional ownership.

FactSet/LionShares data feeds leading financial information providers such as Reuters and

MSN Money. Additionally, The Bank of New York (www.adrbny.com) and J.P. Morgan

(www.adr.com) also rely on FactSet/LionShares as the source for institutional holdings of

ADRs.

FactSet/LionShares data sources are public filings by investors, companies, and security

regulatory agencies around the world. Institutions have discretionary control over assets

under management and are frequently required to publicly disclose their holdings. For secu-

rities traded on major U.S. exchanges, FactSet/LionShares gathers institutional ownership

information via the mandatory 13F filings with the Securities and Exchange Commission

(SEC) as well as by “rolling up” the sum of shares held by the individual mutual funds

(N-30D filings with the SEC) managed by a particular fund management company. Fact-

Set/LionShares also uses the “rolling up” method to gather ownership data for securities

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that are traded outside the U.S. (i.e., shares traded in local markets). Additionally, a data

collection center in France facilitates the collection of ownership data from non-U.S.-based

sources, such as European and offshore mutual funds, stock exchange announcements, data

feeds, proxies, and annual reports. Finally, it uses data frommutual fund industry directories

(e.g., European Fund Industry Directory) and national regulatory agencies, and a variety of

other proprietary resources.

We use the historical filings of the FactSet/LionShares database. The historical coverage

extends from January 2000 to December 2004. We consider all types of stock holdings

(ordinary shares, preferred shares, ADR, GDR, and dual listings) and handle the issue

of different report frequency by institutions from different countries by getting the latest

holdings update at each quarter-end. The data comprises institutions located in 27 different

countries (K) and stock holdings from 48 destination countries stock markets (J).2 This

data set offers a unique worldwide K ×J panel data (when aggregated at the country-level)for each quarter over the 2000-2004 period. As of December 2004, FactSet/LionShares has

holdings data on each of 25,502 stocks worldwide, of which 18,474 are issued outside the U.S.,

for a total market value of US$ 6.8 trillion. The holdings are for each of 22,111 individual

funds run by a total of 3,031 different institutions (such as mutual fund companies, pension

funds, bank management divisions, and insurance companies). To our knowledge, this is the

most comprehensive data set on worldwide institutional equity holdings available.

To summarize the coverage of the institutional holdings data, Table A.1 in Appendix A

presents the total equity assets held by institutions domiciled in each country at the end of

each of the sample years from 2000 to 2004. U.S.-based institutions are by far the largest

group of professional managers of equity assets. When we detail the top five institutions by

equity assets under management (i.e., the largest 13F entities) in December 2004, we find2For a group of 21 other countries (including Argentina, Brazil, China, and Czech Republic) Lion-

Shares/FactSet does not have institutional holdings coverage but contains stock holdings from foreign insti-tutions on local stocks. We keep these foreign stock positions in our tests, but the main results of the paperdo not change if we restrict the sample to the 27 countries for which both institutions and stocks coverageis available. These results are available from the authors upon request.

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leading mutual fund families such as Fidelity, Capital Research and Management, Vanguard,

and Wellington, but also the largest U.S. pension fund manager, TIAA-CREF. Other coun-

tries with large institutional investors are the U.K., Germany, Canada, and France followed

by other countries for a total of 27 countries for which FactSet/LionShares gathers institu-

tional stock holdings data. Most of the leading managers in each country are well-known

financial institutions. While some of countries’ leading fund managers are divisions of banks

like Deutsche Bank’s DWS in Germany, or CDC IXIS and BNP Paribas in France, in other

countries the largest equity managers are public-run funds: Canada Pension Plan or Ontario

Teacher’s Pension Plan in Canada; State’s Petroleum Fund managed by Norges Bank in

Norway. The domicile of the managing institution and of the individual fund can differ as

shown by the large number of international funds, and relatively less institutions, that are

domiciled in Luxembourg.

FactSet/LionShares comprises holdings of domestic and foreign stocks for institutions

across all countries listed in Table A.1. To summarize the stock allocations by origin country

of the institution (in row) and destination country stock market (in column), Table A.2

presents the holdings data in matrix form. Institutions covered by FactSet/LionShares in

December 2004 as a whole managed a total of US$ 6.8 trillion of equity assets of which US$

2.7 trillion are holdings in non-U.S. stocks (i.e., excluding the U.S. as destination market -

the first column in the matrix).

Focusing on all non-U.S. destination markets, we find that domestic institutional investors

with a market value of holdings of US$ 829 billion (the sum of the diagonal elements of the

matrix) are on equal footing to U.S. foreign institutions with US$ 944 billion (the sum of

values on first row of the matrix) and non-U.S. foreign institutions with US$ 927 billion (the

sum of off-diagonal elements). See also the last column of Panel A of Table A.3. Thus, on

aggregate, non-U.S. firms across the world attract money from three institutional investor

clienteles with similar pocket sizes. For example, French firms (column “FR” of Table A.2)

attract a total of US$ 261 billion investment from institutional investors, led by French-based

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institutions (US$ 77 billion — row “FR” of Table A.2), followed by U.S.-based asset managers

(US$ 66 billion — row “US”) and institutions from Germany and the U.K. that add up to

another US$ 69 billion. This example illustrates how the three type of institutional investors

(domestic, U.S., and non-U.S. foreign) are equally important as shareholders for corporations

around the world.

Panel B of Table A.3 shows the fraction of each country’s stock market capitalization

that is held by institutions. FactSet/LionShares institutional stock ownership is the greatest,

as expected, in the U.S. stock market, but global institutional portfolio managers hold large

fractions of stock market capitalization in countries such as Sweden (32.9%), Canada (23.8%),

Denmark (20.9%), and Norway (20.5%). However, not all shares issued by corporations can

be held by institutions, as a significant fraction is closely-held by large shareholders in some

countries. Correcting for the aggregate percentage of closely-held shares (available from

WorldScope), we compute in Panel C the investable market float per country. If we consider

the percentage of market float held by institutional investors, countries such as Norway

(45.1%), Sweden (41.7%), Denmark (33.4%), U.S. (31.7%), Canada (29.5%), and Germany

(27.0%) present the highest institutional ownership.

The presence of domestic relative to foreign institutions varies across countries, for exam-

ple foreign institutions matter more in France (7.2% of market float is in hands of domestic

managers versus 17.4% in foreigners) than in the Sweden (27.2% in domestic versus 14.5%

in foreigners). And when we breakdown into U.S. institutions versus non-U.S. foreign insti-

tutions, U.S. investors are relatively more present in France (6.2%) than in Sweden (5.8%).

To provide a feel of the data, we take the specific cases of the largest French company (Total

SA) and the largest Swedish (Ericsson Telefon AB) as of December 2004 and list their top

five institutional investors:

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Total SA Ericsson Telefon AB

Market capitalization = US$ 138 billion Market capitalization = US$ 48 billion

Total institutional ownership = 30% Total institutional ownership = 33%

Top five institutions (country, % held): Top five institutions (country, % held):

. CDC IXIS Asset Mgt (FR, 2.2% local) . Robur Fonder (SE, 2.7% local)

. Fidelity Mgt (U.S., 1.2% ADR) . Fidelity Mgt (U.S., 1.7% ADR)

. Capital Research & Mgt (US, 0.9% local) . Alecta Pensionsforsaking (SE, 1.7% local)

. Norges Bank (NO, 0.7% local) . Nordea (SE, 1.5% local)

. Wellington (U.S., 0.7% ADR) . SEB Fonder (SE, 1.3% local)

This example illustrates how these companies have domestic, U.S., and foreign non-U.S.

institutions among their leading shareholders. Also, investors opt differently to have their

holdings through local shares or ADRs.

To better understand how comprehensive the FactSet/LionShares data coverage is and

some of its potential limitations, we perform some comparisons with country-level aggre-

gate statistics on institutional equity holdings around the world. These sources include

the OECD official institutional investor survey statistics (OECD (2003b)) and international

mutual fund industry statistics (such as the Federation Europeenne des Fonds et Societes

d’Investissement (FEFSI) statistics used in Khorana et al. (2005), the ShareWorld/Thomson

Financial Securities (TFS) data used in Chan et al. (2005), and the European Fund and Asset

Management Association (2005) statistics). For most countries, the equity holdings reported

in FactSet/LionShares are less than the OECD aggregate numbers for all institutions cat-

egories but exceed just the mutual fund-sicav industry segment. For example, the market

value of equity holdings reported by FactSet/LionShares in 2004 of US$ 6.7 trillion is below

the total OECD value of US$ 9.4 trillion (calculated as total institutional holdings times the

percentage allocation in equity markets) but above the figures for just mutual funds of US

$5.9 trillion in Khorana et al. (2005) or US $4.9 trillion in Chan et al. (2005). There is some

variation in the size of institutional holdings between different data sets due to different con-

10

ventions in terms of institutions type and classification, but overall the FactSet/LionShares

data presents a good coverage.

Second, we analyze how representative are the cross-border equity holdings in Fact-

Set/LionShares relative to aggregate cross-border equity investments statistics. The Coor-

dinated Portfolio Investment Survey (CPIS) conducted by the International Monetary Fund

contains the most comprehensive aggregate information on cross-border holdings but, un-

fortunately, includes the equity holdings of all types of investors and not just institutional

investors (13-F type asset managers), which we analyze in this paper. Still, the CPIS pro-

vides a magnitude for the level of cross-border equity holdings. In 2003, CPIS reports a

total of US$ 2.1 trillion invested by U.S. investors overseas in non-U.S. firms versus US$

3.6 trillion invested by other foreign (non-U.S.) investors in non-U.S. firms. Naturally, these

figures exceed the US$ 0.9 trillion for U.S. holdings in non-U.S. firms and US$ 0.8 trillion

for non-U.S. foreign holdings in non-U.S. firms reported in FactSet/LionShares for the insti-

tutional segment. Given that institutions have a greater presence in the U.S. than in other

countries, it seems justified that the FactSet/LionShares data is somewhat U.S.-tilted. If we

compare to the TFS data (Chan et al. (2005)) on mutual funds cross-border holdings, the

equivalent figures are US$ 0.7 trillion for U.S. holdings in non-U.S. firms and US $0.4 trillion

for non-U.S. foreign holdings in non-U.S. firms, i.e., both figures below the ones reported in

FactSet/LionShares. Thus, the data used in this paper reflects better than previous papers

the average institutional investor of corporations around the world, namely the importance

of non-US investors, but does not include the full extent of holdings (non-institutional seg-

ment).

Finally, the domestic bias implicit in the FactSet/LionShares data is very much in line

with levels found in CPIS and TFS data at the country-level. The domestic bias (cal-

culated as the logarithm of the ratio of the percentage invested domestically by institu-

tions to the market weight of the domestic stock market in the world market) reported

by FactSet/LionShares is intermediate between the level found in the CPIS and TFS data

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(Chan et al. (2005)). For example, for U.S. investors the domestic bias is 64.2% in Fact-

Set/LionShares, which is between 70.5% for all investors in CPIS and 60.3% reported for

just mutual funds in TFS. Domestic bias by origin country of institution are presented in

Panel D of Table A.3.

A more detailed comparison of the FactSet/Lionshares data with the country-level ag-

gregate statistics described earlier is available from the authors upon request.

2.2. Determinants of Institutional Ownership

The main focus of the paper is to examine the determinants of the level of institutional

ownership of firms around the World. We consider both firm-level and country-level char-

acteristics that attract or deter institutional investment as suggested by different streams of

research.

2.2.1. Firm-Level Characteristics

Institutional Trading and Investing Strategies: A first factor determining institu-

tional investment is institutional “preferences”. While this seems somewhat circular, what

we mean is that there are some stylized investment policies documented in the context of

the U.S. markets that distinguish institutional investors from other types of investors (such

as individuals). There are reasons to expect that some of these preferences are also revealed

internationally. However, when an institution invests outside of its domestic stock market

it can behave differently and non-U.S. institutions can act differently from U.S. institutions

as they operate in distinct environments. The major “institutional preferences” previously

documented are the following:

• Firm Size (SIZE): Invest in large stocks. The preference for large firms is documentedin Falkenstein (1996) and Gompers and Metrick (2001) who find stock market capital-

ization to be a major driver of the level of institutional (and mutual fund) ownership

in the U.S. market. Dahlquist and Robertsson (2001) find similar preferences in the

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Swedish market. Size could be even more of a factor in international investment than

it is in the US market because of greater concerns that investors have over liquidity

and transaction costs.

• Book-to-Market (BM): Invest in value stocks. Gompers and Metrick (2001) suggestthat more sophisticated investors such as institutions can exploit the value anomaly.

Thus, institutions should invest in high book-to-market stocks to earn higher excess

returns. Gompers and Metrick (2001) find weak evidence (although increasing over

time) of institutions favoring value stocks. We explore whether this investment strategy

is pursued internationally.

• Investment Opportunities (INV OP ): Invest in growing firms. The higher the realinvestment prospects of a firm, the more likely is to draw institutional investors’ at-

tention. A measure used in the literature is the annual sales growth rate as in Doidge

et al. (2004) and Durnev and Kim (2005). We investigate whether global institutional

investors are attracted by firms with stronger investment opportunities (and probably

more need for external financing).

• Past Return (RET ): Chase recent outperforming stocks. Institutions are potentiallymomentum investors. First, there is some evidence and industry knowledge of the

"momentum effect" in return patterns, i.e., abnormal returns can be obtained by hold-

ing stocks that have performed well in recent times (Gompers and Metrick (2001)).

In addition, many observers depict foreign institutions as “hot money” chasing “hot

markets”, while domestic investors tend to be contrarian investors (Grinblatt and Kelo-

harju (2000)). We entertain this possibility by verifying whether stocks with high re-

cent stock returns (past 12-month) attract higher investment from foreign institutions

relative to domestic institutions.

• Stock Market Turnover (TURN): Invest in liquid stocks. Institutions demand moreliquidity in their investments than other investors because of being delegated portfolio

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managers. They prefer stocks that have a deeper market, where they can enter and

exit easily (Gompers and Metrick (2001)).

”Prudent-Man” Rules: Due to the fiduciary responsibility fund managers have to the

ultimate owners of the assets they manage, many managers are constrained by ”prudent

man” rules that are designed to limit the risk of their investments. These can be just a

set of best practice rules or actual formal investment restrictions written in management

mandates. Del Guercio (1996) studies this in the U.S. context and documents that prudence

considerations are more important for bank-managed funds than mutual funds. Even though

not uniformly across types of funds and, certainly, across different markets (e.g., U.S. versus

German funds), all funds’ investment policies are potentially constrained. The following are

some of the rules that are expected to direct fund managers investment decisions:

• Dividend Yield (DY ): Invest in dividend-paying stocks. For example, many endow-ments in the U.S. have explicit policies to spend only their ”investment income”, which

is many times the money generated by dividends paid by stocks in fund’s portfolio,

instead of partial liquidations of assets. Gompers and Metrick (2001) find that, in con-

trast, U.S. mutual funds seem to be averse to stocks with high dividend yields. In the

international context, foreign investors can have a particular dislike of high dividend-

paying stocks because of dividend tax withholding issues (Dahlquist and Robertsson

(2001) and Ammer et al. (2005)).

• Return-on-equity (ROE): Invest in profitable firms. Because of the oversight by end-investors, many asset managers are under pressure to justify their choice of stock

investments. One common indicator to justify an investment choice to ultimate fund

owners of funds is a stock’s past profitability.

• Stock Price Idiosyncratic Volatility (SIGMA): Invest in low risk stocks. Fiduciarymotives can make money managers “prudently” avoid very risky stocks. Gompers

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and Metrick (2001) find conflicting evidence in the U.S. as institutions tend to prefer

stocks with high volatility. Moreover, there is a literature that interprets idiosyncratic

volatility as a measure of stock price efficiency (Roll (1988) and Morck, Yeung, and Yu

(2000)). Moreover, high-levels of idiosyncratic volatility have been linked to good cor-

porate investment decision-making (Durnev, Morck, and Yeung (2004)) and to a lower

probability of expropriation of outside investors by insiders (Jin and Myers (2006)).

In this sense, institutional investors could reveal a preference for more efficient stocks,

i.e., with higher idiosyncratic volatility.

• MSCI Membership (MSCI): Invest in MSCI member stocks. The asset managementindustry is characterized by ”indexation”, whether explicit (as in index funds) or im-

plicit (as in that funds performance is benchmarked by a market index). Thus, institu-

tions can have a tendency to invest more in index-member stocks. The Morgan Stanley

Capital International (MSCI) All Country World Index is the leading index used in

international asset management. Foreign investors are likely to overweight stocks that

are members of the MSCI index. We investigate whether domestic institutions, in

contrast, fill the void in non-MSCI stocks.

Firm Governance Indicators: Institutions can be particularly responsive to firm-level

governance indicators. Several aspects of the ownership and financial structure of firms can

attract or repel institutional investors:

• Leverage (LEV ): Institutions invest in firms with less debt. Firms with more outstand-ing debt have less need for outsider oversight. As large investors, institutional investors

are potentially outside monitors of managers’ actions (Gillan and Starks (2003)). Thus,

we expect to find lower institutional ownership in firms that currently have high levels

of debt, and where managers actions are monitored by major debtholders.

• Cash (CASH): Institutions invest in cash-rich firms. Managers of firms with morecash are potentially more liable to engage in value-reducing activities (the ”agency

15

costs of free cash flow” in the Jensen (1986) sense). We explore whether institutional

investors avoid or invest in firms with high levels of cash.

• Fraction of Closely Held Shares (CLOSE): Institutional investors avoid firms withdominant shareholders. Institutional investors tend to hold less shares of firms where

one insider or a group of insiders own a large block of shares. Moreover, institutional

investors can actively avoid firms with concentrated ownership because their interests,

as minority shareholders, can be seconded to those of main blockholders. Leuz et al.

(2005) find that U.S. investors invest less in foreign firms with poor governance (i.e.,

with concentrated ownership).

• Corporate Governance Quotient (CGQ): Institutional investors avoid firms with weakinternal governance. Firms with weak governance structures and practices are more

likely to expropriate outside investors. In our empirical tests we use the comprehen-

sive ranking from Institutional Shareholder Services (ISS), which assists institutional

investors in evaluating the quality of corporate boards and of governance practices

(e.g., board of directors, audit, charter and bylaw provisions, laws of the state of in-

corporation, executive and director compensation, qualitative factors, ownership, and

director education).

Presence and Visibility of the Firm in World Markets: One particular determinant

of (foreign) institutional investment is investor recognition, as suggested by market segmen-

tation theories (Merton (1987)) − investors have limited information about just a subset ofstocks and direct their investments to these stocks.

• American Depositary Receipt (ADR): Institutional investors prefer to invest in cross-listed firms. The U.S. cross-listing decision is potentially motivated by firms’ efforts

to increase information on their stock, spur analyst following (Lang, Lins, and Miller

(2003)), and a way of attracting investment by U.S. investors (Foerster and Karolyi

16

(1999)). We only consider exchange-listed ADRs (level 2 and 3) as only these firms are

required to follow U.S. GAAP (and face corresponding stricter disclosure requirements)

as well as SEC stricter reporting and compliance requirements. Cross-listing can be a

magnet for U.S. investors but can also attract non-U.S. institutions. In contrast, we

do not expect to find a cross-listing effect for domestic institutional investors as they

are familiar with local firms prior to the cross-listing.

• Foreign Sales (FXSALES): Institutional investors invest in firms that sell their prod-ucts abroad. A firm that conducts business abroad is more likely to have its name

known among foreign investors and thus induce these investors to consider investing

in the firm’s stock. This argument follows from empirical evidence on the effects of

"familiarity" in investment decisions.

• Analyst coverage (ANALY STS): Institutional investors are attracted to invest infirms with high analyst coverage. The number of analysts following a stock is commonly

considered as an indicator of the firm’s visibility in the market. Analyst coverage can

also be related to the extent to which information is incorporated into stock prices,

though whether analysts contribute with firm-specific or just market-wide information

is a controversial issue (e.g., Piotroski and Roulstone (2004)).

2.2.2. Country-Level Characteristics

The attractiveness of the destination country where the firm is located is likely to be a

substantial factor in foreign investors’ decisions. We explore country-level characteristics

in addition to firm-level characteristics as determinants of institutional ownership. Several

country factors also drive the volume of assets managed by domestic institutions in each

market.

Investor Protection: Foreign institutional investors are likely to prefer to invest in coun-

tries where their minority shareholder interests are protected (La Porta, Lopez-de-Silanes,

17

and Shleifer (2005), and Leuz et al. (2005)). Stronger laws and regulations are a ma-

jor determinant of the overall level of domestic capital markets development (La Porta,

Lopez-de-Silanes, Shleifer, and Vishny (1998)), and of the importance of domestic institu-

tional investors. Khorana et al. (2005) find that legal factors are important determinants of

the size of mutual fund industry around the world.

• Legal (LEGAL): Institutional investors prefer to invest in firms from country with

good legal conditions. We measure the strength of the country’s legal environment

using the product of the anti-director rights index (La Porta et al. (1998)) and the

rule-of-law index following previous literature (e.g., Durnev and Kim (2005)). In-

vestors could avoid stocks of firms located in countries with weak legal environment

and investor protection as they face a higher probability of expropriation by insiders.

• Common Law (COMMON): Institutional investors prefer countries with a commonlaw origin. The legal tradition of the country (common versus civil law) has been

widely considered an indicator of the level of shareholder protection. Countries with

common law are frequently thought to provide shareholders a high degree of protection

(La Porta et al. (1998)).

• Disclosure (DISC): Institutional investors prefer countries with strong financial re-porting and transparency. The disclosure score proxies for the country-level of ac-

counting transparency. Following Jin and Myers (2006), the source of the disclosure

score is the Global Competitiveness Reports for 1999 and 2000, which include results

from surveys about the level and effectiveness of financial disclosure in different coun-

tries, ranging from one to seven. Low values for disclosure are associated with low

levels of transparency.

Distance/Familiarity: Markets that are closer in terms of geographical distance or share

a common language are likely to be overweighted by investors in their international invest-

ments, as shown by mutual fund country-level allocations in Chan et al. (2005).

18

• Geographic Distance (DISTANCE): Institutional investors prefer to invest in firmslocated in countries that are geographically close. More remote countries are likely to

draw less foreign investment.

• English Language (ENGLISH): Institutional investors prefer to invest in English-speaking countries. One barrier to international investment is language. English is the

international language of business. Investors from English-speaking countries, such as

U.K. and U.S., can be more attracted by this feature relative to other foreign investors.

Size and Development of a Country’s Capital Market: The size and level of de-

velopment of a country’s capital market can be a magnet for investment in stocks of that

country (Chan et al. (2005)). Alternatively, however, investors from developed markets may

prefer to invest abroad in emerging markets because of diversification benefits and growth

opportunities. We consider the following proxies for the level of economic and financial

development (e.g., Doidge et al. (2005)):

• GDP Per Capita (GDP ): Institutional investment is higher in more economically

developed countries.

• Stock Market Capitalization as % of GDP (MCAP ): Institutional investment is higherinto countries with larger stock markets or more financially developed countries.

Table B.1 in Appendix B details the definitions and data sources for each of the variables

introduced in this section.

2.3. Sample of Firms and Summary Statistics

The firm-level financial data are drawn from Datastream (DS, stock market data) andWorld-

Scope (WS, accounting data) for the years of 2000 through 2004. The initial sample includes

all firms in the WS database excluding financial firms (SIC code between 6000-6999). We

merge this sample of firms with the institutional holdings data from FactSet/LionShares at

19

the end of each calendar year using alternatively SEDOL codes (only for non-U.S. firms),

CUSIP codes (only for U.S. firms), or ISIN codes.

We use many different data sources to construct our ADR data set and determine which

non-U.S. firms are cross-listed in the U.S., when they have initiated and ended their ADR

programs, or the type of ADR (e.g., listed in an exchange or unlisted). Data on non-U.S. firms

listing in the U.S. market (NYSE, Nasdaq, AMEX, over-the-counter, and Rule 144a) with

an ADR or ordinary listing are obtained from the primary depository institutions: Citibank,

Bank of New York, JP Morgan, and Deutsche Bank. Each of these institutions have part of

the information, and no individual database includes all ADR programs actually available.

We add to this information data collected directly from the stock exchanges on the non-U.S.

listings (including Canadian and Israeli firms that list directly in the U.S. exchanges).

We sum the holdings of all institutions in a firm’s stock at the end of each calendar year

and divide it by the end-of-year market capitalization. Thus, our variable of interest is the

fraction of shares held by institutional investors with a breakdown by domestic institutions

(i.e., institutions domiciled in the same country in which the stock is issued), and foreign

institutions (i.e., institutions domiciled in a country different from the one where the stock

is issued). We further breakdown foreign holdings into U.S. and non-U.S. domiciled asset

managers. Later, we also perform the empirical analysis using only firms with positive

holdings and explicit zero holdings. The primary results are not affected. We aggregate

local shares and ADR positions per firm to have the total stock ownership regardless of the

share type. Following Gompers and Metrick (2001), if a stock is not held by any institution

in FactSet/LionShares, we set institutional ownership variables to zero. We also examine

institutional positions in local and ADR positions separately in subsection 3.3 below.

Our final sample includes 15,656 unique firms, of which we mainly focus on 10,951 non-

U.S. firms, for a total of 31,382 firm-year observations for which we have data for the main

variables of interest (we winsorize financial ratios, such as return-on-equity and leverage,

at the bottom and top 1% levels). Table 1 provides summary statistics of institutional

20

ownership variables, and firm- and country-level control variables for non-U.S. firms. The

average non-U.S. firm in the sample has a market capitalization of US$ 146 million, 14.6%

are MSCI index members, and 3.8% are cross-listed in an U.S. exchange. About 38% of

the observations are from English-speaking countries. Average institutional ownership by

domestic institutions is 2.7% for non-U.S. firms but this is an equally-weighted average and we

know from previous studies that institutional ownership is higher among large firms. Indeed,

in the last column of Panel B of Table A.3, we can see that total institutional ownership for

the sample of non-U.S. firms is 13.7%. Furthermore, as discussed in subsection 2.1, when we

correct for shares that are closely-held, total institutional ownership is 22.7% (see Panel C

of Table A.3).

3. Institutional Ownership and Firm and Country Char-

acteristics

This section reports the results of the cross-sectional determinants of the level of institutional

ownership worldwide. The first subsection presents our main tests with respect to what

firm and country-level characteristics attract institutional investors. The second subsection

contains several robustness checks and extensions of our main results. The final subsection

contains an analysis of the ADR effect, or whether an U.S. cross-listing is able to attract a

foreign investor clientele.

3.1. What Attracts Foreign and Domestic Institutions?

Table 2 presents the main tests on which firm- and country-level characteristics matter the

most in attracting different types of institutional investors, as we discussed in Subsection

2.2. In our regressions, we focus on non-U.S. firms (Panel A of Table 2). Panel A has four

subpanels for each group of investors whose fraction of total ownership we explain: all foreign

institutions (U.S. plus non-U.S. money managers), only U.S.-based institutions, only non-

21

U.S.-based foreign investors, and domestic institutions (i.e. managers domiciled in the same

country where the firm’s stock is listed). For each subpanel we estimate three specifications:

(1) with just firm-level variables; (2) with both firm and country-level variables; and (3) with

firm-level variables and country fixed effects.

The main results of Panel A (non-U.S. firms) in general support the conjectured effects

on “institutional preferences”. We find that, on average, institutional investors around the

world, whether foreign or domestic, have a preference for large firms (SIZE) with liquid

shares (TURN). But the three different groups of managers also display diverse investment

behavior in terms of other stock characteristics. U.S. institutions prefer value stocks (high

BM), while non-U.S. foreign and domestic institutions prefer growth stocks. U.S. institutions

are also more prone to chase stocks with recent positive stock return performance (RET ) than

are non-U.S. institutions, and domestic investors seem to have a contrarian behavior. All

institutions seem to load on stocks with strong profitability indicators (ROE and INV OP ),

reflecting some of the “prudent man” rules they are subject to in their investment decisions.

Against these rules, however, foreign institutional investors seem to dislike high-dividend

paying stocks, in contrast to domestic institutions, perhaps for the taxation issues mentioned

earlier. Foreigners do not shy away from high idiosyncratic volatility stocks (SIGMA).

Institutional investors seem to react to firm-level governance practices when they decide

to invest in a firm. Institutions hold less shares of firms that are closely held or with

concentrated control rights (CLOSE), with high levels of debt (LEV ), and with high levels

of cash (CASH). Some of these results are consistent with the role of institutional investors

as outside monitors advocated by the literature on investor activism (e.g., Gillan and Starks

(2003)). Leuz et al. (2005) also find that U.S. investors invest less in poorly governed firms,

namely those whose ownership structures are more conducive to governance problems and

expropriation by controlling managers and families.

Both U.S. and other foreign investors have a bias for companies that are members of the

MSCI index (MSCI), and that have cross-listed their shares in an U.S. exchange (ADR).

22

The positive MSCI coefficient indicates the importance of this international benchmark for

foreign investors. Thus, there is evidence that international institutional investors load on

index members. The negativeMSCI coefficient for domestic institutions indicates that this

investor group fills the void in non-MSCI stocks in their home market. The positive ADR

coefficient for both U.S. and non-U.S. foreign institutional investors illustrates the positive

effect exerted by the cross-listing on their investment decisions. This finding is consistent

with the results in Ammer et al. (2005) and Aggarwal et al. (2005) for U.S. investors. It is also

consistent with related evidence in Lang et al. (2003) that document an increase in analyst

coverage when a firm cross-lists in an U.S. exchange. This is consistent with increased

institutional interest and higher visibility for firms that cross-list in the U.S. Because of

selection bias issues (i.e., firms with higher foreign ownership are more likely to cross-list),

we analyze in more depth this cross-listing effect in Subsection 3.3 below. In contrast, when

investing domestically, institutions do not seem to prefer firms with ADRs.

In terms of country-level variables, all institutions reveal a preference for stocks of coun-

tries with good disclosure standards (DISC) and that are geographically closer to their

local market (DISTANCE). U.S. institutions show a clear preference for English-speaking

countries (ENGLISH), common-law countries (COMMON), and less developed mar-

kets (MCAP ), while non-U.S. investors make relatively more investments in non-English-

speaking countries and more developed markets when they invest abroad. These findings

illustrate that these groups of institutional investors have different reasons for investing

abroad. Good disclosure standards (DISC) and legal environment (LEGAL) are found to

increase the presence of domestic institutional investors, but we find opposite results for in-

vestor protection with respect to attracting foreign institutions. This is inconsistent to what

the law and finance literature would suggest (La Porta et al. (1998)). Our interpretation

is that investors decision to go abroad balances weak shareholder protection against strong

investment prospects or diversification benefits. This argument explains why U.S. investors

prefer emerging markets to European markets when investing overseas.

23

One important observation from Table 2 is that our results show that firm-level character-

istics have substantial explanatory power over country-level variables for foreign institutional

ownership. As we can be seen by comparing the first specification (including only firm-level

variables) with the second specification (including firm- and country-level variables) in each

subpanel, the increase in R2 of adding country-level variables is marginal in the first three

subpanels for foreign ownership. Institutional investors do more than just country-level

portfolio allocations: They engage in specific stock picking based on firm characteristics. In

the last subpanel for domestic institutional ownership in non-U.S. firms, however, country

factors are particularly important to explain the cross-sectional variation. This finding is

consistent with the idea that the size and development of the domestic institutional investor

segment is related to the country’s overall quality of institutions (Khorana et al. (2005)).

Panel B of Table 2 considers the level of U.S. institutional investment in U.S. stocks.

This is not at the core of our investigation but is more of a “benchmarking” exercise. Our

results replicate previous findings by Gompers and Metrick (2001). Like these authors, we

find a preference for large and liquid stocks with “value” orientation. As described earlier,

U.S. institutions have similar stock preferences when investing abroad.

Table 3 extends the previous results on institutional investors preferences in terms of

firm’s foreign visibility and the quality of governance mechanisms. We address in more detail

the role of firm’s visibility by adding as explanatory variables the percentage of foreign sales

(FXSALES) and the number of analysts covering a firm (ANALY STS). We add these

variables separately in the first and second specification in each panel of Table 3 because of

data availability that reduces substantially the sample size. The following findings, however,

are not affected by including these variables simultaneously. We find that firm’s “name” and

visibility abroad entice foreigners to hold more shares as shown by the positive and significant

coefficients in the first three subpanels for foreign ownership. The last subpanel for domestic

institutional ownership in non-U.S. firms shows a differential investment behavior. There is

evidence that firm’s visibility indicators are not as important when institutional investors

24

invest at home, i.e., in familiar stocks. There is even some evidence that domestic investors

tend to underweight highly-visible firms.

The third specification in each panel of Table 3 extends the previous results in terms of

the role of firm-level corporate governance quality in investors decisions. We include the ISS

corporate governance ranking (CGQ) as additional explanatory variable.3 We find that the

corporate governance ranking is important for domestic investor but foreigners seem not to

care about these rankings, in contrast to visibility indicators. Domestic institutional investors

show a preference for firms with good corporate governance mechanisms and practices as

shown by the positive and significant CGQ coefficient. In the next subsection, we further

explore the role of firm-level corporate governance in determining institutions preferences.

In particular, we analyze in more detail whether firm-level governance can have different

impact on the revealed preferences of institutional investors depending on the country-level

quality of institutions and investor protection.

Lastly, we analyze in more detail the different stock investment preferences of the three

institutional investor groups. Table 4 estimates the determinants of the difference in insti-

tutional ownership between foreign and domestic institutions (first column) and U.S. versus

non-U.S. foreign institutions (second column) on the sample of non-U.S. firms. Specifically,

the dependent variables are, respectively, the difference between total foreign and domes-

tic institutional ownership of a firm’s stock, and the difference between U.S. institutional

ownership and non-U.S. foreign institutional ownership.

Table 4 shows that preference for size is more pronounced on foreign than on domestic

institutional holders. Similarly, for other factors already disentangled in Table 2, we find

that foreigners (relative to domestic) are biased towards stocks with high liquidity, with a

“value” orientation, that are members of an MSCI index, and that cross-list their shares in

the U.S. market. In the second column, we document differences in preferences between U.S.

and non-U.S. institutions and find that U.S. investors have a higher (relative) preference for3Once again, to maximize the sample size we do not include FXSALES and ANALY STS as controls.

Results including all variables are consistent with those reported in Table 3.

25

value stocks and firms with ADRs, but (relatively) lower preference for large firms, MSCI

members, and that are closely-held. Non-U.S. and U.S. portfolio managers venture into

countries with different legal environments and different locations.

3.2. Robustness Checks and Extensions

We now check the robustness of our main results of the previous subsection by conducting

several alternative regression specifications. The first issue we tackle in Panel A of Table

5 is the measurement of institutional ownership as a fraction of shares that are not closely

held (or float) instead of as a fraction of all shares. As documented in Dahlquist, Pinkowitz,

Stulz, and Williamson. (2003), firms in many countries around the world have large fractions

of their shares that are closely held by blockholders, so there are fewer shares available to

outside investors. We control for this issue in the regressions of Table 2 using the closely held

shares variable (CLOSE). Indeed, CLOSE has a significant negative coefficient in Table 2,

meaning that institutional investors as minority shareholders have smaller fraction of shares

of firms with high insider stakes. An alternative way to account for this issue, however, is to

scale institutional ownership by the total market float instead of the total market capitaliza-

tion. We rescale all four institutional ownership variables (foreign, U.S., non-U.S. foreign,

and domestic) by one minus CLOSE. Panel A of Table 5 presents the results of the own-

ership regressions using the float scaling. Overall, the results corroborate the main findings

of Subsection 3.1 with respect to what firm characteristics attract institutional investors.

Institutional investors have a demand for large and liquid stocks when they decide to invest,

but there is also substantial diversity in other stock preferences among the three groups of

institutions. Foreigners weight positively MSCI membership and U.S. cross-listing, while

domestic institutions weight negatively these same stocks. There are also some significant

country-level factors (e.g., U.S. institutions prefer to invest in English-speaking countries),

but the main part of the cross-sectional variation is explained by firm-level characteristics

A second issue is that there are a considerable number of firms that have zero institu-

26

tional ownership in at least one of our ownership variables (all foreign, U.S., non-U.S. foreign,

and domestic). Because of this potential censoring of the dependent variable in our OLS

results in Table 2, we estimate alternatively a Tobit model. Panel B of Table 5 reports the

results that are mainly in line with our previous findings regarding commonality and diver-

sity in institutional stock preferences (size, liquidity, dividends, value/growth, momentum,

profitability, MSCI membership, and cross-listing) among the three groups of institutions.

A third issue is to consider an alternative definition of our dependent variable. We

alternatively take the ratio of the stock weight in the institutions portfolio relative to the

stock weight in the world market portfolio. A positive ratio implies that institutions invest

disproportionately more in a stock relative to the market portfolio (institutions overweight

the stock), while a negative ratio implies that institutions invest less in a stock relative to

the market portfolio (institutions underweight the stock). Panel C of Table 5 reports the

results that are consistent with our main findings. Institutions overweight large, liquid, and

widely held stocks, but there is also diversity in other stock preferences among U.S., non-U.S.

foreign, and domestic institutions. Foreign institutions overweight firms that are members

of the MSCI index and with U.S. cross-listing, while domestic institutions underweight stock

of these same firms.

Our results are also robust in other ways. In unreported regressions, we have run year-

by-year regressions like those in Table 2 and find that main results are stable over the

sample years. We have also estimated regressions like those in Table 2 using the logarithm

of ownership as dependent variable, including industry and year dummies, using a sample

of firms from only the countries for which institutional holdings are available, and only

including the observations with positive or explicit zero institutional holdings. These results

(not tabulated here) are consistent with our primary findings.

To conclude this subsection, we extend our previous results in two important ways:

What is the role of geographical location of firms and investors in explaining the level of

institutional ownership? How does country-level investor protection interact with firm-level

27

characteristics to determine institutional holdings?

We find that familiarity has an important role in institutional investment decisions.

Specifically, institutions tend to prefer firms to which they are geographically close. Thus,

we explore in more detail the geography of cross-border investments with results presented in

Table 6. Within non-U.S. firms, we isolate out firms listed in Asian (Panel A) and European

(Panel B) markets. We then breakdown foreign institutional investors based also on their

geographic origin: Asia, Europe, or North America. We can spot some regional patterns:

European investors do not hold more European stocks when the firm has an ADR program,

but they hold more stocks in the case of Asian firms with ADRs. North American investors,

however, seem always to prefer firms with ADRs, regardless the firms is located in Europe

or Asia. These findings strongly support the investor recognition hypothesis for European

institutional investors as they prefer to invest in visible stocks (e.g., stocks with ADR pro-

grams) when they invest abroad, while these characteristics are not relevant when they are

investing in familiar (European) stocks. The MSCI membership seems to be significant for

investor preferences regardless of whether they are investing in a stock market geographically

close to their home or investing overseas.

We extend our results to consider the role of country-level quality of institutions or

investor protection in explaining the investment preferences of institutional investors around

the world. We focus, in particular, on how investor protection impacts the institutions’

preferences with respect to investor recognition variables (MSCI and ADR) and firm-level

governance aspects (CLOSE and CGQ). Our hypothesis is that investor recognition and

the quality of the firm-level corporate governance are particularly important in countries

with weak investor protection. In strong investor protection environments, we expect that

the importance of these firm-level characteristics as determinants of investor’s preferences is

considerably mitigated.

Table 7 presents results in which we include an interaction between these firm-level vari-

ables and the country’s investor protection level as measured by the LEGAL variable. We

28

consider two separate specifications because the CGQ variable has a limited number of obser-

vations. Results indicate that institutional investors dedicate special attention to firm-level

characteristics when they decide to invest in countries with weak environments (i.e., coun-

tries that score low in terms of the LEGAL variable), especially when they decide to invest

abroad. We find that the interaction of the LEGAL variable with the MSCI or ADR

variables presents, with few exceptions, a negative and significant coefficient. The interpre-

tation is that the preference revealed by foreign institutions for stocks that are members of

the MSCI index and cross-listed in the U.S. is attenuated in countries with strong investor

protection. In other words, for firms located in countries with weak investor protection,

MSCI membership, and cross-listing are significant boosters of foreign institutional owner-

ship. With respect to firm-level governance, we find that foreigners avoid firms with major

controlling shareholders and weak governance practices, especially when these firms operate

in environments with weak investor protection. This finding is supported by the positive and

significant coefficient of the CLOSE × LEGAL interaction variable and the negative andsignificant coefficient of the CGQ×LEGAL interaction variable in the first three subpanelsfor foreign ownership. The results for domestic investors confirm that this group presents a

distinct behavior with respect to these firm-level characteristics. Unreported regression re-

sults using alternatively the country’s legal origin (COMMON) in place of LEGAL confirm

the primary findings in Table 7.

3.3. A Detailed Analysis of the Cross-listing Effect

Results throughout Tables 2 to 7 seem to indicate that foreign investors, both U.S. as well

as from other countries, have a distinct preference for holding firms that cross-list in an U.S.

exchange. However, firms that decide to cross-list in the U.S. might be those that would

have higher foreign ownership irrespective of the cross-listing event, so we want to isolate

the extra boost in foreign ownership that is related with the cross-listing decision.

The first methodology employed to correct econometrically for this selection bias in our

29

regressions is the “treatment effects” model (Greene (2003), chapter 22). We estimate jointly

the equation of our interest, institutional holdings, with the propensity of a non-U.S. firm

cross-lists its shares in an U.S. exchange, using a two-step estimator:

(Institutional Holdings)j,t = X0j,tβX + δ(ADR)j + ej,t, (1)

Prob(ADRj) = Z0j,tβZ + nj,t. (2)

Note that identification of the model parameters requires at least one instrument that

is related to institutional holdings (enters in Xj,t of equation (1)), but does not determine

the decision to cross-list (does not enter in Zj,t of equation (2)). We identify the system

by considering some of the “institutional preference” variables (stock return, dividend yield,

return-on-equity, and MSCI membership) that are usually not considered as determinants

of cross-listing decision by previous research (e.g., Doidge et al. (2004)).

Table 8 presents the results. We focus particularly on the coefficient of the ADR dummy

variable on institutional ownership variables in each panel (all foreign institutions, U.S. insti-

tutions, non-U.S. foreign institutions, and domestic). Our previous results are confirmed as

cross-listing give an additional boost for U.S. institutions and non-U.S. foreign institutions

to invest in a firm’s stock (consistent with the predictions of Foerster and Karolyi (1999)

among others). In total, foreign investors hold an extra 5% of the market capitalization of

firms that have an ADR than they would otherwise, even after one corrects for the selection

bias of cross-listing decision. In contrast, we see that domestic institutions actually fill the

void in non-ADR stocks. Estimated coefficients on other explanatory variables in institu-

tional ownership regression are in line with previous results. In terms of the Probit model

results (equation (2)) presented in the first column, we find that firms are more likely to

cross-list in the U.S. if they are large, widely-held, and come from countries with weak legal

environments. These results are in line with the findings in Doidge et al. (2004) and Ammer

30

et al. (2005).

The second, and perhaps more direct, method to isolate out the cross-listing effect is

to study the dynamics of the institutional ownership structure following the cross-listing

event. Given that we have a sizeable panel data set, we can identify 101 firms that have

cross-listed their shares in an U.S. exchange during our sample period between January

2000 and December 2004. We compare the level of foreign institutional ownership in the

quarters around the cross-listing. We thus treat all cross-listings in event time and present

the median foreign institutional ownership in the quarters before and after the cross-listing

event in Panel B of Table 9. We see that, although foreign investors hold local shares of those

firms prior to the cross-listing, they substantially increase their total position from 1.75% of

firm’s market capitalization at quarter -1 to 7.40% in quarter +8. We can conclude that firms

that cross-list their shares in the U.S. experience an increase in their foreign institutional

shareholder base of about 5.65 percentage points (from quarter -1 to quarter 8).

The FactSet/LionShares data allows us to break down holdings into those in local shares

(i.e., direct investments in firms’ shares in its market of origin) and those in ADR shares. As

we can observe in Panel B of Table 9 the increase in foreign institutional ownership mainly

occurs in local shares holdings rather than in the ADR shares directly. This finding sheds

light on the “flow-back” phenomenon of ADRs, i.e., after an initial blip in U.S. trading of

ADR shares, trading moves back to the more liquid domestic exchange (Karolyi (2003) and

Halling et al. (2004)). Even though trading is not retained by the U.S. exchanges, cross-

listed firms get extra foreign investors on board (both U.S. and non-U.S.) who are making

the trip to the firm’s home market and invest in the local shares. Interestingly, it is not only

US institutions that increase their holdings on local shares of firms that cross-list, but also

foreign non-US institutions.

31

4. Institutional Ownership and Firm Valuation

This section investigates the relation between institutional ownership (foreign and domestic)

and a firm’s valuation. As in the previous section on investor’s preferences, we focus on

non-U.S. firms. Our goal is to test whether the presence of foreign institutions in a firm’s

shareholder base has real effects in terms of effectively reducing the firm’s cost of capital.

We first report the results of regressing a firm’s Tobin’s Q on foreign institutional ownership.

Next, we handle the potential endogeneity issue that firm valuations and ownership are

jointly determined so we estimate a system of simultaneous equations for ownership and

firm’s valuation using three-stage least squares.

To investigate the relation between institutional ownership and firm valuation, we adopt

Tobin’s Q as the valuation measure (as in, for example, Doidge et al. (2004) and Durnev and

Kim (2005)) computed as follows. For the numerator, we add the book value of total assets

to the market value of equity, and subtract book value of equity. For the denominator, we use

total assets. In Table 10, we regress a firm’s Tobin’sQ on variables associated with firm value

such as SIZE, growth opportunities (INV OP ), leverage (LEV ), cash holdings (CASH),

whether a firm is cross-listed in an U.S. exchange (ADR), and median industry Tobin’s Q for

the firm’s global industry. We also include country-level variables that are usually related

with firm’s valuation in the literature such as the legal regime index (LEGAL). Mostly

important, we extend this firm valuation equation by including our variable of interest: The

level of foreign (PF ) and domestic (PD) institutional ownership. The first three columns

consider, respectively, the ownership of all foreign institutions, U.S. institutions, non-U.S.

foreign institutions. The last column considers domestic institutional ownership as well as

control variables. In unreported regressions, we include industry, country, and year dummies

without significant impact on the primary results.

Results in Table 10 show that firms with higher foreign institutional ownership have

higher valuations. The PF coefficient is positive and statistically significant. In contrast,

there is no evidence that higher domestic institutional is associated with higher valuations

32

as shown by the negative PD coefficient. These results provide evidence of the real effects

of a firm’s shareholder base including foreign institutional investors. Ownership by foreign

investors seems to drive up firm valuations (and thus potentially reduce the firm’s cost of

capital).Having controlled for either foreign or domestic institutional ownership, we do not

find a direct ADR valuation premium.

Our results offer a direct link between foreign (institutional) shareholder presence and

firms’ valuations. Our findings support the idea that the expansion of the foreign institutional

ownership base is one of the channels by which cross-listing in the U.S. market reduces

firms’ cost of capital as documented by Doidge et al. (2004). An alternative interpretation

of our findings, however, is that firms that attract foreign investors can become overvalued.

Recent literature argues that firm valuation benefits of internationalization are transitory

and dynamic (Levine and Schmukler (2005) and Sarkissian and Schill (2005)), and mainly

accrue before the cross-listing. Other control variables coefficients are in general consistent

with predictions and existing literature. Large cash-rich firms with investment opportunities

have higher valuations. More levered firms have lower valuations.

Institutional ownership is likely to be jointly determined with the firm’s valuation and

driven by similar characteristics. To address this concern, we re-estimate the Tobin’s Q

and institutional ownership equations as a system of simultaneous equations using three-

stage least squares. Identification is achieved by the independent variables included in the

ownership equation that are not related to Tobin’s Q.

Table 11 reports the results that also include the usual country-level controls. We find

that the positive effect of foreign institutional ownership on Tobin’s Q ratios is robust to

endogeneity concerns. Over our sample period, we find that for a 1% rise in foreign institu-

tional ownership, a firm’s Tobin’s Q would rise, on average, by 2.36%. Overall, the results

using three-stage least squares regression corroborate the findings in Table 10 with respect

to the valuation effects of attracting foreign institutional investors and expanding the firm’s

shareholders base. The results in Table 11 (Panel B) also confirm that the expansion of the

33

foreign institutional ownership base is one of the channels by which cross-listing in the U.S.

market reduces firms’ cost of capital.

5. Conclusion

In this paper we study the stock holdings of institutional investors around the world using

a novel database that spans the 2000-2004 period. Our data contains a total of US$ 2.6

trillion invested in non-U.S. stocks, of which US$1.8 trillion are cross-border investments, as

of December 2004. We analyze non-U.S. stock-level investments by domestic, U.S.-based, and

non-U.S.-based foreign institutions. We show these three investor groups have equal sized

pockets, and thus we offer a global (non-U.S. centric) view of what attracts international

institutions to invest in corporations around the world. Our tests show that the three groups

of institutional investors exhibit a demand for large and liquid stocks with good governance

practices, but they also exhibit divergent preferences in their investment decisions. There is

substantial diversity in other stock preferences (dividends, value/growth, momentum, and

volatility) among the three groups of institutions. Moreover, foreigners weight positively

MSCI membership and firms that cross-list their shares in an U.S. exchange. There are also

some relevant country-level factors (e.g., U.S. investors prefer English-speaking destinations),

but the main part of the cross-sectional variation is explained by firm-level characteristics,

suggesting that outside investors care about which particular firms to pick instead of just

following country-level allocations.

We analyze how successful are efforts by firms to tap into foreign capital by the mean of an

ADR program. We document that U.S. cross-listing is associated with an increase in foreign

institutional ownership, both from U.S. and other countries foreign institutions. Analyzing

the change in foreign institutional ownership around the time of a cross-listing, we uncover

that the increase does not occur only in ADR stocks but also in foreign holdings of shares in

the firm’s local market. This sheds light on the puzzling “flow-back” of volume back to the

34

firms’ home market quickly after an ADR listing. Instead of “flow-back” being a symptom of

a failure to capture foreign investors, our results show that it occurs concurrently with many

of the new foreign investors making the trip to the firm’s homemarket. This is one illustration

of how modern international capital markets operate where firm and investor actions take

place in connected markets. The extra information and analyst coverage stemming from

an U.S. listing can provide a significant boost to foreign ownership of local shares around

the world. This finding adds to the explanations of multi-market trading of internationally

cross-listed stocks.

Our third main finding is that foreign ownership is positively associated with higher

firm valuations. This is consistent with an increased investor base lowering the firm’s cost

of capital or better expected cash flows perhaps by better outside monitoring provided by

these institutions. Alternatively, investor price pressure can cause some temporary stock

overvaluation. Distinguishing between these two alternative effects is an important issue,

in light of some of the recent evidence on the transient and dynamics of benefits of firms’

internationalization. We leave this issue for future work.

One other avenue for future research is to analyze how firms’ financing activities interact

with institutional ownership. One instance is to study other cross-listings beyond ADR

programs, to document whether European or Asian firms regional cross-listings tap into

regional pools of capital, as suggested by proximity preference evidence in Sarkissian and

Schill (2004). A related avenue for future research is how firms’ international capital raising

activities, as studied recently by Henderson, Jegadeesh, and Weisbach (2005), is determined

by the particular pool of investors currently holding a firms’ shares or the potential ones the

firm is trying to tap into. These and other relevant research questions can be explored with

the novel international ownership data set we use in this paper.

35

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40

Table 1Summary Statistics

This table reports mean, median, standard deviation, maximum, minimum, and number of observations (N) ofvariables for non-U.S. firms. All variables are as defined in Appendix B. The sample period is from 2000 to 2004.Financial firms are omitted (SIC 6000-6999).

Variable Mean Median Std Dev Min Max NPanel A: Institutional Ownership Variabes (firm-level)

Foreign ownership all institutions PF 0.024 0.002 0.052 0.000 0.804 31382Foreign ownership US institutions PFUS 0.011 0.001 0.030 0.000 0.571 31382Foreign ownership non-US institutions PFNUS 0.013 0.000 0.033 0.000 0.635 31382Domestic ownership all institutions PD 0.027 0.000 0.069 0.000 0.930 31382

Panel B: Firm-Level Control VariabesMarket capitalization (log) SIZE 11.892 11.783 1.930 4.787 19.418 31382Book-to-market (log) BM -0.181 -0.157 0.902 -3.425 3.255 31382Investment opportunities INV OP 0.103 0.048 0.299 -0.848 2.899 31382Stock return annual RET 0.000 0.000 0.005 -0.025 0.016 31382Turnover TURN 0.682 0.326 1.143 0.000 10.387 31382Dividend yield DY 0.022 0.015 0.025 0.000 0.145 31382Return-on-equity ROE 0.029 0.058 0.277 -3.424 1.252 31382Idiosyncratic variance SIGMA 0.172 0.095 0.243 0.000 3.752 31382MSCI membership dummy MSCI 0.146 0.000 0.353 0.000 1.000 31382Leverage LEV 0.256 0.241 0.180 0.000 1.032 31382Cash CASH 0.124 0.088 0.124 0.000 0.902 31382ADR listed dummy ADR 0.038 0.000 0.192 0.000 1.000 31382Closely held shares CLOSE 0.461 0.464 0.233 0.000 0.984 31382Foreign sales FXSALES 0.411 0.370 0.281 0.000 1.000 13426Analysts coverage ANALY STS 6.611 4.000 6.578 1.000 48.000 17532Corporate governance ranking CGQ 0.506 0.507 0.279 0.001 0.999 4960Tobin’s Q Q 1.333 1.077 0.955 0.406 17.808 32910Global industry Tobin’s Q GLOBAL_Q 1.225 1.142 0.279 0.834 3.014 32910

Panel C: Country-Level Control VariablesLegal regime quality index LEGAL 29.055 34.280 12.122 0.000 50.000 31382Common law dummy COMMON 0.383 0.000 0.486 0.000 1.000 31382Disclosure index DISC 5.602 5.600 0.627 3.700 6.500 31382Average distance (log) DISTANCE 8.929 9.055 0.250 8.340 9.568 31382English language dummy ENGLISH 0.383 0.000 0.486 0.000 1.000 31382GDP per capita (log) GDP 9.761 10.145 1.076 6.094 11.005 31382Market capitalization to GDP MCAP 1.040 0.816 0.737 0.046 3.749 31382

41

Table 2Determinants of Foreign and Domestic Institutional Ownership

Panel A reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-U.S. firms foreign ownership by all institutions, U.S. institutions and non-U.S.institutions, and non-U.S. firms domestic ownership as a percentage of market capitalization. Panel B reports estimates of coefficients of the annual time-series cross-sectional firm-levelregression for U.S. firms domestic ownership as a percentage of market capitalization. The firm-level regressors include equity capitalization (SIZE), book-to-market equity ratio (BM),investment opportunities (INV OP ), stock return (RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membershipdummy (MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares (CLOSE). Some specifications include alternatively country dummiesor country-level regressors. The country-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON), disclosure index (DISC), average geographicdistance (DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 in Appendix B for variabledefinitions. The sample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are in boldface.

Panel A: Non-US Firms Panel B:US Firms

Variable Pred. Foreign Ownership Foreign Ownership Foreign Ownership Domestic DomesticSign All Institutions US Institutions Non-US Institutions Ownership Ownership

Constant -0.0492 0.0541 -0.0264 -0.0090 -0.0230 0.0622 0.0330 0.8014 -0.1969(-21.59) (4.74) (-19.58) (-1.38) (-15.00) (8.17) (10.70) (46.61) (-27.04)

SIZE + 0.0067 0.0067 0.0069 0.0035 0.0038 0.0038 0.0032 0.0029 0.0032 0.0032 0.0044 0.0045 0.0315(35.92) (32.63) (33.31) (30.52) (28.63) (28.77) (27.11) (23.08) (24.65) (14.42) (18.29) (18.75) (53.60)

BM + -0.0008 0.0008 0.0002 0.0004 0.0016 0.0009 -0.0012 -0.0008 -0.0007 -0.0104 -0.0003 -0.0017 0.0140(-2.31) (2.22) (0.55) (2.24) (7.59) (4.23) (-5.09) (-3.25) (-2.76) (-23.79) (-0.81) (-4.04) (11.13)

INV OP + 0.0064 0.0055 0.0037 0.0017 0.0009 -0.0002 0.0049 0.0048 0.0041 0.0072 0.0021 -0.0006 -0.0255(6.47) (5.51) (3.79) (3.42) (1.77) (-0.51) (6.53) (6.40) (5.58) (4.80) (1.55) (-0.43) (-9.41)

RET + 0.0170 0.1998 0.1750 0.0999 0.1114 0.1253 -0.0825 0.0881 0.0489 -0.5191 -0.4315 -0.3608 0.5147(0.30) (3.49) (3.13) (3.12) (3.45) (4.00) (-2.10) (2.27) (1.28) (-6.04) (-5.43) (-4.72) (3.41)

TURN + 0.0008 0.0010 0.0008 -0.0002 0.0003 -0.0001 0.0011 0.0008 0.0009 -0.0040 0.0017 0.0012 0.0210(3.38) (4.02) (2.71) (-1.55) (2.41) (-0.46) (5.78) (4.04) (4.41) (-20.69) (8.55) (6.22) (19.33)

DY + -0.0283 -0.0440 -0.0541 -0.0128 -0.0357 -0.0270 -0.0161 -0.0089 -0.0275 0.1966 0.0784 0.0891 -1.1286(-2.71) (-4.01) (-4.89) (-2.03) (-5.17) (-4.22) (-2.40) (-1.31) (-3.80) (10.72) (4.72) (5.43) (-17.27)

ROE + 0.0078 0.0071 0.0062 0.0028 0.0031 0.0020 0.0050 0.0040 0.0042 0.0058 0.0085 0.0084 0.0134(7.44) (6.88) (6.07) (4.63) (5.25) (3.42) (6.84) (5.59) (5.91) (3.65) (5.85) (5.84) (4.92)

SIGMA - 0.0048 0.0045 0.0030 0.0027 0.0012 0.0002 0.0022 0.0033 0.0028 0.0119 0.0020 0.0015 -0.0288(4.51) (4.06) (2.75) (4.99) (2.23) (0.33) (2.59) (3.79) (3.29) (7.44) (1.44) (1.11) (-12.90)

MSCI + 0.0232 0.0243 0.0230 0.0103 0.0106 0.0100 0.0129 0.0136 0.0129 -0.0177 -0.0134 -0.0110(17.84) (18.93) (18.34) (13.25) (13.88) (13.57) (15.96) (17.23) (16.55) (-15.13) (-12.58) (-11.29)

LEV - -0.0099 -0.0058 -0.0078 -0.0038 -0.0004 -0.0023 -0.0062 -0.0055 -0.0055 -0.0304 -0.0004 -0.0048 -0.0024(-6.76) (-3.86) (-5.30) (-4.35) (-0.44) (-2.67) (-6.44) (-5.61) (-5.76) (-15.23) (-0.21) (-2.72) (-0.43)

CASH + 0.0093 0.0151 0.0144 0.0068 0.0110 0.0101 0.0025 0.0042 0.0044 -0.0316 0.0047 0.0000 -0.0369(3.93) (6.12) (6.08) (4.49) (6.77) (6.40) (1.77) (2.87) (3.10) (-9.20) (1.46) (-0.00) (-5.74)

ADR + 0.0330 0.0307 0.0279 0.0212 0.0199 0.0191 0.0117 0.0107 0.0087 -0.0044 -0.0147 -0.0170(12.64) (11.80) (11.17) (12.41) (11.54) (11.77) (8.52) (8.01) (6.53) (-2.60) (-8.90) (-10.49)

CLOSE - -0.0252 -0.0264 -0.0289 -0.0147 -0.0114 -0.0114 -0.0105 -0.0150 -0.0175 -0.0780 -0.0437 -0.0338 -0.0805(-19.74) (-19.55) (-20.26) (-20.28) (-15.42) (-14.90) (-12.35) (-16.54) (-18.06) (-40.66) (-26.95) (-20.14) (-17.69)

LEGAL + -0.0006 -0.0001 -0.0004 0.0010(-12.47) (-6.06) (-13.64) (22.54)

COMMON + -0.0015 0.0027 -0.0040 0.0062(-1.50) (3.87) (-6.90) (8.02)

DISC + 0.0093 0.0034 0.0060 0.0219(8.29) (5.84) (7.69) (21.53)

DISTANCE - -0.0157 -0.0048 -0.0108 -0.0954(-14.04) (-7.03) (-15.48) (-54.52)

ENGLISH + -0.0005 0.0038 -0.0045 0.0196(-0.50) (6.34) (-7.01) (19.50)

GDP + -0.0001 0.0005 -0.0006 -0.0106(-0.16) (1.43) (-1.38) (-20.42)

MCAP + 0.0022 -0.0008 0.0030 -0.0100(4.14) (-2.43) (9.12) (-20.21)

Country dum. No No Yes No No Yes No No Yes No No Yes NoR2 0.2230 0.2457 0.2994 0.1789 0.1893 0.2515 0.1433 0.1872 0.2336 0.1158 0.2871 0.3582 0.4256N 31382 31382 31382 31382 31382 31382 31382 31382 31382 31382 31382 31382 14867

42

Table 3Determinants of Foreign and Domestic Institutional Ownership: The Role of Visibility and Governance

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-U.S. firms foreign ownership by all institutions, U.S. institutions andnon-U.S. institutions, and non-U.S. firms domestic ownership as a percentage of market capitalization. The firm-level regressors include equity capitalization (SIZE), book-to-marketequity ratio (BM), investment opportunities (INV OP ), stock return (RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCIindex membership dummy (MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), closely held shares (CLOSE), international sales (FXSALES), analyst coverage(ANALY STS), and corporate governance ranking (CGQ). The country-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON), disclosureindex (DISC), average geographic distance (DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to TableB.1 in Appendix B for variable definitions. The sample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are in boldface.

Variable Pred. Foreign Ownership Foreign Ownership Foreign Ownership Domestic OwnershipSign All Institutions US Institutions Non-US Institutions

Constant 0.0056 0.1622 -0.0026 -0.0210 0.0230 -0.0389 0.0232 0.1393 0.0364 0.9489 0.9991 0.9817(0.27) (8.83) (-0.05) (-1.75) (2.47) (-1.26) (1.78) (10.91) (1.05) (34.17) (40.24) (24.52)

SIZE + 0.0072 0.0022 0.0040 0.0042 0.0019 0.0031 0.0031 0.0003 0.0009 0.0043 0.0020 -0.0045(22.41) (5.55) (4.95) (20.35) (8.15) (7.10) (15.49) (1.14) (1.71) (10.20) (4.58) (-6.21)

BM + -0.0016 0.0000 -0.0024 0.0008 0.0018 0.0008 -0.0024 -0.0018 -0.0033 -0.0021 0.0003 -0.0008(-2.54) (0.03) (-1.76) (2.14) (5.45) (1.07) (-5.41) (-4.26) (-3.63) (-2.68) (0.46) (-0.69)

INV OP + 0.0058 0.0091 0.0156 -0.0001 0.0023 0.0065 0.0062 0.0068 0.0091 -0.0010 0.0009 -0.0044(3.23) (5.45) (2.88) (-0.08) (2.67) (2.14) (4.37) (5.74) (2.88) (-0.39) (0.43) (-1.13)

RET + -0.0014 0.5903 0.2271 0.0434 0.3208 0.3102 -0.0492 0.2715 -0.0831 -0.3837 -0.1695 -0.3191(-0.02) (6.44) (1.04) (0.93) (6.64) (2.41) (-0.82) (4.24) (-0.61) (-3.00) (-1.42) (-1.95)

TURN + 0.0007 0.0023 0.0198 0.0005 0.0007 0.0079 0.0003 0.0016 0.0119 0.0008 0.0026 0.0031(1.20) (4.78) (7.54) (1.47) (3.15) (5.08) (0.88) (4.52) (8.14) (1.59) (7.51) (2.10)

DY + 0.0013 -0.0206 -0.0495 -0.0039 -0.0280 -0.0262 0.0044 0.0072 -0.0233 0.2249 0.0794 0.1169(0.07) (-1.13) (-0.84) (-0.33) (-2.58) (-0.78) (0.38) (0.62) (-0.64) (7.03) (2.94) (2.16)

ROE + 0.0091 0.0090 0.0179 0.0037 0.0038 0.0111 0.0054 0.0052 0.0068 0.0081 0.0064 -0.0065(4.91) (4.50) (3.09) (4.24) (3.44) (4.18) (3.93) (3.78) (1.66) (3.12) (2.54) (-1.56)

SIGMA - 0.0001 -0.0003 -0.0235 -0.0010 -0.0022 -0.0103 0.0011 0.0019 -0.0132 0.0000 0.0010 0.0130(0.04) (-0.10) (-3.06) (-1.01) (-1.98) (-2.07) (0.64) (0.87) (-3.06) (0.02) (0.35) (1.65)

MSCI + 0.0194 0.0147 0.0145 0.0080 0.0059 0.0051 0.0112 0.0088 0.0095 -0.0168 -0.0090 0.0028(10.74) (10.42) (7.12) (7.22) (7.34) (4.28) (10.38) (9.97) (7.79) (-9.77) (-7.37) (1.81)

LEV - -0.0076 -0.0084 -0.0227 -0.0002 -0.0005 -0.0084 -0.0074 -0.0078 -0.0143 -0.0089 -0.0034 -0.0071(-2.68) (-3.66) (-4.16) (-0.15) (-0.42) (-2.57) (-3.97) (-5.19) (-4.38) (-2.67) (-1.25) (-1.78)

CASH + 0.0113 0.0198 0.0362 0.0120 0.0134 0.0344 -0.0007 0.0064 0.0018 0.0009 0.0100 0.0110(2.75) (5.07) (3.30) (4.58) (5.75) (4.91) (-0.27) (2.57) (0.32) (0.17) (1.97) (1.41)

ADR + 0.0222 0.0263 0.0217 0.0157 0.0194 0.0132 0.0063 0.0070 0.0085 -0.0266 -0.0142 -0.0061(6.86) (9.48) (6.30) (7.11) (10.34) (6.42) (3.89) (4.91) (4.27) (-11.38) (-7.58) (-2.35)

CLOSE - -0.0379 -0.0337 -0.0407 -0.0143 -0.0147 -0.0165 -0.0235 -0.0190 -0.0242 -0.0535 -0.0446 -0.0329(-16.75) (-16.04) (-8.00) (-11.92) (-13.00) (-5.82) (-15.31) (-13.45) (-7.49) (-19.35) (-18.22) (-8.58)

FXSALES + 0.0199 0.0075 0.0126 0.0014(11.39) (7.70) (11.00) (0.65)

ANALY STS + 0.0021 0.0009 0.0012 -0.0002(17.81) (12.13) (17.55) (-1.86)

CGQ + -0.0014 -0.0023 0.0009 0.0126(-0.31) (-0.90) (0.31) (3.81)

LEGAL + -0.0005 -0.0004 -0.0011 -0.0001 -0.0001 -0.0004 -0.0004 -0.0003 -0.0008 0.0015 0.0012 0.0011(-7.11) (-5.59) (-7.70) (-3.79) (-2.21) (-4.45) (-7.54) (-6.45) (-8.53) (19.64) (19.00) (10.47)

COMMON + -0.0053 -0.0114 -0.0188 0.0026 -0.0024 -0.0001 -0.0074 -0.0090 -0.0187 0.0162 0.0074 0.0007(-2.73) (-6.28) (-2.84) (1.99) (-2.13) (-0.03) (-6.12) (-8.14) (-4.83) (9.12) (5.78) (0.21)

DISC + 0.0118 0.0082 0.0373 0.0050 0.0029 0.0132 0.0069 0.0053 0.0241 0.0281 0.0284 0.0371(4.82) (4.61) (8.04) (3.80) (3.45) (5.22) (4.08) (4.15) (8.21) (14.20) (17.62) (11.86)

DISTANCE - -0.0127 -0.0207 -0.0109 -0.0053 -0.0057 -0.0087 -0.0073 -0.0151 -0.0022 -0.1175 -0.1169 -0.1209(-6.49) (-12.18) (-1.95) (-4.43) (-5.71) (-2.59) (-6.16) (-13.98) (-0.72) (-41.63) (-47.76) (-30.11)

ENGLISH + -0.0060 0.0026 -0.0092 0.0010 0.0068 0.0032 -0.0074 -0.0041 -0.0124 0.0142 0.0215 0.0074(-3.59) (1.45) (-1.71) (0.91) (6.54) (1.00) (-6.84) (-3.51) (-4.13) (9.20) (14.21) (3.07)

GDP + -0.0001 -0.0014 -0.0091 0.0004 -0.0001 0.0023 -0.0004 -0.0013 -0.0115 -0.0100 -0.0125 -0.0048(-0.06) (-1.49) (-1.97) (0.53) (-0.12) (0.97) (-0.41) (-2.04) (-3.81) (-7.91) (-15.08) (-1.64)

MCAP + 0.0044 0.0024 0.0145 0.0002 0.0004 0.0048 0.0042 0.0020 0.0097 -0.0144 -0.0116 -0.0066(4.91) (2.49) (6.35) (0.48) (0.72) (3.61) (7.08) (3.26) (6.62) (-18.39) (-13.45) (-5.22)

R2 0.2876 0.2601 0.2716 0.2178 0.2023 0.1985 0.2328 0.2082 0.2542 0.3304 0.3244 0.4201N 13426 17532 4960 13426 17532 4960 13426 17532 4960 13426 17532 4960

43

Table 4Determinants of Foreign versus Domestic Ownership and US versus Non-US

Foreign Owership

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for the differencebetween foreign and domestic institutional ownership in non-U.S. firms and the difference between non-U.S. and U.S. in-stitutional foreign ownership in non-U.S. firms as a percentage of market capitalization. The firm-level regressors includeequity capitalization (SIZE), book-to-market equity ratio (BM), investment opportunities (INV OP ), stock return (RET ),turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membershipdummy (MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares (CLOSE).The country-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON), disclosureindex (DISC), average geographic distance (DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ),and market capitalization to GDP (MCAP ). Refer to Table B.1 in Appendix B for variable definitions. The sample periodis from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are in boldface.

Variable Difference of Foreign Difference of US toto Domestic Ownership Non-US Foreign Ownership

Constant -0.7473 -0.0712(-37.53) (-8.61)

SIZE 0.0023 0.0008(8.05) (5.33)

BM 0.0012 0.0024(2.26) (8.74)

INV OP 0.0034 -0.0039(2.07) (-5.08)

RET 0.6313 0.0232(6.83) (0.54)

TURN -0.0007 -0.0004(-2.39) (-2.20)

DY -0.1225 -0.0268(-6.49) (-3.27)

ROE -0.0013 -0.0008(-0.81) (-1.04)

SIGMA 0.0024 -0.0020(1.40) (-2.19)

MSCI 0.0377 -0.0029(24.94) (-3.36)

LEV -0.0054 0.0051(-2.49) (4.55)

CASH 0.0104 0.0068(2.73) (3.70)

ADR 0.0453 0.0091(15.85) (5.48)

CLOSE 0.0173 0.0035(9.04) (3.70)

LEGAL -0.0016 0.0003(-27.21) (8.83)

COMMON -0.0076 0.0067(-6.36) (8.37)

DISC -0.0125 -0.0026(-8.74) (-3.35)

DISTANCE 0.0798 0.0060(39.74) (7.43)

ENGLISH -0.0201 0.0084(-15.00) (11.21)

GDP 0.0105 0.0010(14.29) (2.39)

MCAP 0.0122 -0.0038(17.94) (-9.93)

R2 0.2193 0.0515N 31382 31382

44

Table 5Robustness Checks of Determinants of Foreign and Domestic Institutional Ownership

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firms foreign ownership by all institutions, U.S. institutions and non-U.S.institutions, and non-U.S. firms domestic ownership. Panel A reports estimates considering ownership as a percentage of float. Panel B estimates a Tobit model. Panel C reports estimatesconsidering ownership relative to the market portfolio, i.e., the ratio of the firm’s weight in institutions portfolios by the firm’s world market weight. The firm-level regressors include equitycapitalization (SIZE), book-to-market equity ratio (BM), investment opportunities (INV OP ), stock return (RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE),idiosyncratic variance (SIGMA), MSCI index membership dummy (MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares (CLOSE). Thecountry-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON), disclosure index (DISC), average geographic distance (DISTANCE), Englishlanguage dummy (ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 in Appendix B for variable definitions. The sample period isfrom 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are in boldface.

Panel A: Ownership as % of Float Panel B: Tobit Model Panel C: Relative OwnershipVariable Pred. Foreign Foreign Foreign Domest. Foreign Foreign Foreign Domest. Foreign Foreign Foreign Domest.

Sign Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner. Owner.All US Non-US All US Non-US All US Non-USInst. Inst. Inst. Inst. Inst. Inst. Inst. Inst. Inst.

Constant 0.1606 -0.0655 0.2236 1.2990 -0.1309 -0.1761 -0.0263 0.8088 1.1468 -0.0921 2.3720 52.4646(2.75) (-2.39) (5.81) (38.71) (-6.71) (-14.45) (-1.60) (22.98) (3.93) (-1.44) (7.38) (44.94)

SIZE + 0.0113 0.0064 0.0050 0.0056 0.0156 0.0098 0.0129 0.0184 0.1692 0.0370 0.1206 0.3094(16.44) (16.26) (11.74) (10.96) (49.38) (49.64) (48.20) (34.45) (30.93) (28.46) (22.31) (18.65)

BM + 0.0078 0.0048 0.0030 0.0014 0.0068 0.0060 0.0025 -0.0030 0.0082 0.0158 -0.0517 -0.1128(5.65) (6.26) (3.49) (1.76) (12.80) (17.68) (5.75) (-3.13) (0.85) (7.49) (-4.76) (-3.91)

INV OP + 0.0111 0.0031 0.0083 0.0066 0.0083 0.0002 0.0112 0.0036 0.1567 0.0088 0.2047 0.1161(4.17) (2.18) (4.64) (2.20) (6.04) (0.28) (9.91) (1.55) (5.88) (1.80) (6.50) (1.22)

RET + 0.8785 0.4537 0.4286 -0.7588 -0.0385 -0.0036 -0.1419 -0.9169 9.2552 1.0613 12.5948 -5.8780(3.81) (3.23) (2.98) (-4.15) (-0.48) (-0.07) (-2.11) (-6.61) (6.04) (3.31) (7.25) (-1.06)

TURN + 0.0022 -0.0003 0.0026 0.0034 0.0026 0.0012 0.0019 -0.0028 0.0159 0.0031 0.0214 0.0787(1.60) (-0.81) (2.25) (11.23) (6.85) (5.13) (6.19) (-2.86) (2.43) (2.29) (2.56) (5.62)

DY + -0.0023 -0.0479 0.0445 0.0824 0.0206 0.0067 0.0305 0.0967 -1.3304 -0.3539 -0.7195 4.7699(-0.04) (-1.53) (1.39) (2.62) (1.15) (0.60) (2.01) (2.89) (-4.70) (-5.18) (-2.49) (4.23)

ROE + 0.0171 0.0086 0.0086 0.0176 0.0121 0.0064 0.0090 0.0135 0.1963 0.0316 0.1616 0.7397(4.18) (3.52) (3.76) (5.49) (7.03) (5.87) (6.14) (4.78) (6.75) (5.27) (5.16) (6.59)

SIGMA - 0.0064 0.0022 0.0043 -0.0006 -0.0004 -0.0032 0.0028 -0.0048 0.1618 0.0126 0.2004 0.3144(1.99) (1.42) (1.80) (-0.21) (-0.21) (-2.41) (1.63) (-1.36) (5.41) (2.34) (4.59) (3.20)

MSCI + 0.0605 0.0263 0.0340 -0.0209 0.0180 0.0076 0.0107 -0.0238 0.5760 0.1043 0.5320 -1.0315(8.46) (6.80) (7.67) (-11.49) (13.97) (9.61) (10.53) (-10.51) (17.57) (13.79) (16.10) (-14.15)

LEV - -0.0126 -0.0024 -0.0102 0.0048 -0.0073 0.0003 -0.0112 -0.0274 -0.1263 -0.0034 -0.2194 0.0100(-1.71) (-0.66) (-2.27) (1.35) (-3.00) (0.20) (-5.53) (-6.41) (-3.13) (-0.38) (-4.95) (0.08)

CASH + 0.0321 0.0202 0.0119 0.0162 0.0300 0.0197 0.0208 0.0237 0.3693 0.1084 0.1399 0.0677(4.01) (4.22) (2.59) (2.69) (8.62) (9.02) (7.21) (4.04) (5.81) (6.76) (2.30) (0.31)

ADR + 0.0741 0.0421 0.0319 -0.0260 0.0253 0.0171 0.0039 -0.0463 0.7435 0.1953 0.4151 -1.0763(4.64) (5.31) (3.54) (-10.41) (12.73) (14.02) (2.51) (-13.26) (11.32) (11.52) (7.49) (-10.00)

CLOSE - -0.0464 -0.0252 -0.0315 -0.0713 -0.6727 -0.1129 -0.6246 -3.1783(-24.51) (-21.21) (-20.06) (-21.27) (-19.77) (-15.44) (-16.81) (-27.27)

LEGAL + -0.0013 -0.0005 -0.0008 0.0014 -0.0004 0.0000 -0.0004 0.0022 -0.0132 -0.0014 -0.0160 0.0656(-9.20) (-6.89) (-8.36) (14.85) (-8.18) (-0.73) (-9.07) (23.71) (-11.76) (-5.97) (-12.85) (21.79)

COMMON + -0.0216 -0.0052 -0.0161 0.0054 -0.0047 0.0024 -0.0089 -0.0198 -0.0681 0.0258 -0.2055 0.2476(-3.96) (-1.56) (-4.96) (3.42) (-2.92) (2.32) (-6.54) (-4.81) (-2.77) (3.77) (-8.11) (4.96)

DISC + 0.0118 0.0077 0.0043 0.0443 0.0124 0.0053 0.0083 0.0616 0.2379 0.0338 0.2558 1.3690(3.01) (3.49) (1.71) (20.29) (8.97) (6.08) (7.37) (23.50) (8.47) (5.93) (7.67) (21.78)

DISTANCE - -0.0235 0.0012 -0.0245 -0.1634 -0.0178 -0.0030 -0.0206 -0.1839 -0.3688 -0.0467 -0.4219 -6.1842(-4.99) (0.40) (-9.57) (-48.19) (-9.43) (-2.54) (-12.98) (-55.47) (-13.16) (-6.96) (-14.55) (-53.01)

ENGLISH + 0.0135 0.0116 0.0015 0.0302 -0.0049 0.0028 -0.0107 0.0479 -0.0347 0.0375 -0.2303 1.3050(3.23) (5.41) (0.60) (15.04) (-2.85) (2.60) (-7.30) (11.64) (-1.39) (6.28) (-8.40) (19.76)

GDP + 0.0605 0.0263 0.0340 -0.0209 0.0066 0.0060 0.0021 0.0211 -0.0110 0.0040 -0.0334 -0.7558(8.46) (6.80) (7.67) (-11.49) (8.42) (12.03) (3.30) (11.68) (-0.76) (1.27) (-1.98) (-21.97)

MCAP + 0.0108 0.0024 0.0085 -0.0157 0.0004 -0.0024 0.0011 -0.0218 0.0900 -0.0074 0.1619 -0.3744(6.72) (2.45) (8.69) (-14.52) (0.60) (-5.78) (1.94) (-18.56) (6.49) (-2.29) (11.23) (-11.10)

R2 0.0605 0.0498 0.0480 0.1882 0.2364 0.1884 0.1750 0.2740N 30291 30291 30291 30291 31382 31382 31382 31382 31382 31382 31382 31382

45

Table 6Determinants of Foreign Institutional Ownership by Geographical Regions

Panel A reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for Asian firms institu-tional foreign ownership as a percentage of market capitalization with breakdown by institution’s geographic region. Panel Breports estimates of coefficients of the annual time-series cross-sectional firm-level regression for European firms institutionalownership as percentage of market capitalization with breakdown by institution’s geographic region. The firm-level regressorsinclude equity capitalization (SIZE), book-to-market equity ratio (BM), investment opportunities (INV OP ), stock return(RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI indexmembership dummy (MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares(CLOSE). The country-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON),disclosure index (DISC), average geographic distance (DISTANCE), English language dummy (ENGLISH), GDP percapita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 in Appendix B for variable definitions. Thesample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are inboldface.

Panel A: Asian Firms Panel B: European FirmsForeign Foreign Foreign Foreign Foreign Foreign

Variable Pred. Owner. Owner. Owner. Owner. Owner. Owner.Sign Asian European North-Amer. Asian European North-Amer.

Inst. Inst. Inst. Inst. Inst. Inst.Constant -0.0569 -0.0368 -0.0848 0.0416 0.2774 0.2223

(-5.14) (-4.21) (-3.41) (3.02) (4.73) (6.52)SIZE + 0.0019 0.0019 0.0033 0.0000 0.0033 0.0039

(12.66) (24.80) (21.78) (-0.22) (14.41) (19.54)BM + 0.0009 -0.0003 0.0011 0.0001 -0.0022 0.0012

(2.91) (-2.02) (4.33) (1.90) (-3.99) (3.06)INV OP + 0.0029 0.0014 -0.0002 -0.0001 0.0054 -0.0009

(4.02) (3.45) (-0.38) (-1.20) (4.01) (-1.19)RET + 0.3236 0.0668 0.1083 0.0018 -0.0295 -0.0036

(6.17) (2.44) (3.09) (0.16) (-0.39) (-0.07)TURN + 0.0013 0.0003 -0.0007 0.0001 0.0045 0.0038

(5.36) (3.22) (-4.38) (1.39) (3.50) (4.05)DY + 0.0428 -0.0195 -0.0257 0.0051 -0.0638 -0.0089

(3.93) (-4.07) (-3.11) (0.59) (-4.97) (-0.76)ROE + 0.0022 0.0017 0.0010 0.0000 0.0061 0.0029

(3.36) (4.06) (2.02) (0.55) (4.69) (3.11)SIGMA - -0.0017 0.0009 0.0008 0.0000 0.0016 -0.0018

(-1.16) (2.01) (1.22) (0.25) (0.86) (-1.63)MSCI + 0.0085 0.0079 0.0109 0.0008 0.0128 0.0094

(8.19) (15.47) (13.66) (3.79) (8.03) (6.58)LEV - -0.0066 -0.0047 -0.0061 -0.0002 -0.0021 0.0050

(-6.84) (-8.70) (-7.48) (-0.96) (-0.86) (2.63)CASH + 0.0089 0.0035 0.0084 -0.0003 -0.0005 0.0098

(4.68) (3.52) (4.94) (-1.19) (-0.17) (3.50)ADR + 0.0061 0.0077 0.0179 0.0000 0.0029 0.0184

(2.35) (5.22) (6.26) (0.12) (1.57) (7.51)CLOSE - 0.0009 -0.0030 -0.0030 -0.0004 -0.0301 -0.0162

(0.70) (-5.12) (-3.32) (-1.27) (-16.80) (-12.33)LEGAL + 0.0000 -0.0001 -0.0008 0.0000 0.0001 0.0000

(-0.69) (-2.15) (-8.25) (3.10) (2.76) (0.89)COMMON + -0.0051 0.0008 0.0024

(-7.16) (2.41) (3.00)DISC + -0.0045 -0.0026 0.0046 -0.0001 0.0019 0.0007

(-3.32) (-4.23) (2.96) (-1.04) (1.16) (0.54)DISTANCE - 0.0063 0.0020 0.0015 -0.0047 -0.0444 -0.0408

(4.39) (1.88) (0.46) (-2.94) (-6.08) (-9.05)ENGLISH + 0.0011 0.0010 0.0040 0.0000 -0.0240 -0.0009

(1.61) (2.71) (6.49) (-0.29) (-14.03) (-0.71)GDP + 0.0008 0.0020 0.0038 0.0001 0.0088 0.0093

(1.68) (8.29) (10.27) (0.31) (5.18) (6.61)MCAP + 0.0025 0.0002 0.0014 -0.0002 -0.0020 0.0000

(7.44) (1.18) (3.51) (-2.86) (-2.36) (0.01)R2 0.0853 0.1927 0.2110 0.0037 0.2057 0.2160N 17839 17839 17839 11758 11758 11758

46

Table 7Determinants of Foreign and Domestic Institutional Ownership: The Role of

Investor Protection

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firmsforeign ownership by all institutions, U.S. institutions and non-U.S. institutions, and non-U.S. firms domestic ownership asa percentage of market capitalization. The firm-level regressors include equity capitalization (SIZE), book-to-market equityratio (BM), investment opportunities (INV OP ), stock return (RET ), turnover (TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membership dummy (MSCI), leverage (LEV ), cash holdings(CASH), ADR listed dummy (ADR), closely held shares (CLOSE), and corporate governance ranking (CGQ). The country-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON), disclosure index (DISC),average geographic distance (DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ), and marketcapitalization to GDP (MCAP ). Refer to Table B.1 in Appendix B for variable definitions. The sample period is from 2000to 2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are in boldface.

Foreign Foreign Foreign DomesticVariable Pred. Ownership Ownership Ownership Ownership

Sign All Inst. US Inst. Non-US Inst.Constant 0.0722 -0.0044 -0.0096 -0.0397 0.0807 0.0353 0.7341 0.9817

(6.26) (-0.08) (-1.43) (-1.30) (10.59) (1.03) (43.54) (24.51)SIZE + 0.0069 0.0038 0.0037 0.0030 0.0032 0.0008 0.0039 -0.0045

(33.07) (4.83) (28.19) (6.98) (24.51) (1.57) (16.20) (-6.21)BM + 0.0008 -0.0031 0.0016 0.0006 -0.0008 -0.0036 -0.0004 -0.0008

(2.14) (-2.25) (7.50) (0.75) (-3.32) (-4.09) (-1.07) (-0.69)INV OP + 0.0053 0.0149 0.0009 0.0062 0.0045 0.0087 0.0023 -0.0044

(5.28) (2.88) (1.83) (2.12) (6.08) (2.83) (1.67) (-1.13)RET + 0.1827 0.2015 0.1112 0.3001 0.0712 -0.0986 -0.4226 -0.3191

(3.21) (0.93) (3.46) (2.36) (1.84) (-0.73) (-5.33) (-1.95)TURN + 0.0010 0.0215 0.0004 0.0086 0.0007 0.0129 0.0024 0.0031

(3.82) (8.19) (2.83) (5.57) (3.48) (8.74) (11.53) (2.11)DY + -0.0448 -0.0492 -0.0356 -0.0260 -0.0098 -0.0231 0.0750 0.1169

(-4.08) (-0.86) (-5.15) (-0.78) (-1.45) (-0.66) (4.57) (2.16)ROE + 0.0069 0.0182 0.0032 0.0112 0.0038 0.0070 0.0091 -0.0065

(6.69) (3.05) (5.26) (4.20) (5.31) (1.65) (6.25) (-1.56)SIGMA - 0.0043 -0.0266 0.0011 -0.0115 0.0033 -0.0151 0.0011 0.0130

(3.95) (-3.48) (2.02) (-2.35) (3.78) (-3.40) (0.82) (1.65)MSCI + 0.0296 0.0127 0.0066 0.0043 0.0229 0.0083 -0.0044 0.0028

(7.82) (6.36) (3.13) (3.70) (9.40) (7.02) (-2.06) (1.82)LEV - -0.0053 -0.0243 -0.0003 -0.0090 -0.0051 -0.0153 -0.0010 -0.0071

(-3.51) (-4.53) (-0.35) (-2.82) (-5.17) (-4.72) (-0.54) (-1.78)CASH + 0.0152 0.0382 0.0112 0.0352 0.0040 0.0031 0.0047 0.0110

(6.16) (3.47) (6.93) (5.01) (2.76) (0.53) (1.47) (1.41)ADR + 0.0570 0.0187 0.0359 0.0120 0.0211 0.0067 0.0193 -0.0061

(7.65) (5.63) (7.79) (6.05) (5.07) (3.45) (6.05) (-2.34)CLOSE - -0.0420 -0.0452 -0.0084 -0.0183 -0.0335 -0.0269 0.0184 -0.0329

(-10.45) (-8.86) (-4.06) (-6.38) (-11.93) (-8.31) (5.39) (-8.54)CGQ + 0.1245 0.0476 0.0769 0.0126

(7.65) (5.40) (7.68) (1.32)LEGAL + -0.0007 0.0003 -0.0001 0.0002 -0.0006 0.0001 0.0021 0.0011

(-8.71) (1.50) (-2.01) (1.93) (-10.97) (0.73) (24.01) (9.05)COMMON + -0.0012 -0.0061 0.0028 0.0049 -0.0039 -0.0110 0.0058 0.0007

(-1.23) (-0.88) (4.03) (1.19) (-6.51) (-2.76) (7.78) (0.20)DISC + 0.0096 0.0355 0.0034 0.0125 0.0063 0.0231 0.0214 0.0371

(8.53) (7.78) (5.83) (4.93) (8.05) (7.98) (21.13) (11.88)DISTANCE - -0.0170 -0.0156 -0.0049 -0.0105 -0.0120 -0.0051 -0.0918 -0.1209

(-15.20) (-2.83) (-7.19) (-3.12) (-17.08) (-1.64) (-53.15) (-30.16)ENGLISH + 0.0002 0.0053 0.0037 0.0089 -0.0038 -0.0037 0.0166 0.0074

(0.19) (0.90) (6.14) (2.57) (-5.82) (-1.13) (16.78) (2.92)GDP + -0.0005 -0.0071 0.0005 0.0031 -0.0010 -0.0103 -0.0097 -0.0048

(-0.91) (-1.60) (1.53) (1.31) (-2.54) (-3.53) (-19.13) (-1.63)MCAP + 0.0017 0.0095 -0.0007 0.0029 0.0025 0.0066 -0.0086 -0.0066

(3.24) (3.99) (-2.28) (2.02) (7.47) (4.36) (-16.94) (-4.85)MSCI × LEGAL - -0.0002 0.0001 -0.0003 -0.0003

(-1.73) (1.92) (-4.97) (-3.68)ADR× LEGAL - -0.0009 -0.0006 -0.0004 -0.0012

(-4.25) (-3.99) (-3.19) (-9.53)CLOSE × LEGAL + 0.0005 -0.0001 0.0006 -0.0022

(4.54) (-1.57) (8.12) (-15.74)CGQ× LEGAL - -0.0043 -0.0017 -0.0026 0.0000

(-8.66) (-6.07) (-8.72) (0.01)R2 0.2492 0.2909 0.1912 0.2084 0.1944 0.2735 0.2961 0.4201N 31382 4960 31382 4960 31382 4960 31382 4960

47

Table 8Foreign and Domestic Institutional Ownership and Cross-Listing: Selection

Bias

The probit regression estimates the probability that a non-U.S. firms cross-lists in an U.S. exchange. The table reports reportsestimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firms foreign ownesrhip byall institutions, U.S. institutions and non-U.S. institutions, and non-U.S. firms domestic ownership as a percentage of marketcapitalization using the ”treatment effects” model (see Greene (2003), chapter 22). The firm-level regressors include equitycapitalization (SIZE), book-to-market equity ratio (BM), investment opportunities (INV OP ), stock return (RET ), turnover(TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membership dummy(MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and closely held shares (CLOSE). Thecountry-level regressors include legal regime index (LEGAL), common law dummy variable (COMMON), disclosure index(DISC), average geographic distance (DISTANCE), English language dummy (ENGLISH), GDP per capita (GDP ), andmarket capitalization to GDP (MCAP ). The Lambda coeficient estimate accounts for the relevance of the selection correction.Refer to Table B.1 in Appendix B for variable definitions. The sample period is from 2000 to 2004. Robust t-statistics are inparentheses. Coefficients significant at the 5% level are in boldface.

Foreign Foreign Foreign DomesticVariable Probit Ownership Ownership Ownership Ownership

All Inst. US Inst. Non-US Inst.Constant -8.4557 0.0484 -0.0041 0.0523 0.7720

(-10.42) (3.77) (-0.53) (6.32) (42.85)SIZE 0.4187 0.0062 0.0034 0.0029 0.0060

(41.97) (27.51) (24.72) (19.39) (19.09)BM -0.0008 0.0014 -0.0022 -0.0010

(-2.36) (6.46) (-9.74) (-2.02)INV OP 0.0850

(1.53)RET 0.0017 0.0012 0.0005 -0.0050

(3.10) (3.72) (1.53) (-6.79)TURN 0.0006 0.0003 0.0003 0.0018

(2.49) (2.09) (1.89) (5.10)DY -0.0005 -0.0003 -0.0001 0.0010

(-3.96) (-4.98) (-1.36) (5.91)ROE 0.0000 0.0000 0.0000 0.0001

(4.62) (2.88) (4.35) (5.14)SIGMA 0.0042 0.0006 0.0036 0.0036

(3.51) (0.89) (4.55) (2.15)MSCI 0.0205 0.0092 0.0115 -0.0108

(22.14) (16.59) (19.04) (-8.48)LEV 0.9035 -0.0071 -0.0014 -0.0055 0.0045

(8.42) (-4.34) (-1.47) (-5.23) (1.98)CASH 1.7218 0.0135 0.0095 0.0039 0.0075

(13.00) (5.69) (6.69) (2.55) (2.26)ADR 0.0532 0.0380 0.0153 -0.0764

(13.50) (16.18) (5.96) (-14.20)CLOSE -0.4474 -0.0282 -0.0113 -0.0167 -0.0446

(-6.02) (-22.15) (-14.73) (-20.31) (-24.96)LEGAL -0.0179 -0.0006 -0.0001 -0.0004 0.0010

(-8.01) (-14.73) (-5.41) (-17.67) (18.13)COMMON -0.2949 0.0005 0.0033 -0.0030 0.0088

(-3.47) (0.45) (5.30) (-4.51) (6.08)DISC 0.7039 0.0092 0.0027 0.0066 0.0298

(12.30) (9.76) (4.75) (10.82) (22.46)DISTANCE 0.1519 -0.0149 -0.0048 -0.0100 -0.0962

(2.04) (-12.15) (-6.52) (-12.64) (-55.88)ENGLISH 0.3029 -0.0022 0.0034 -0.0056 0.0159

(3.30) (-2.03) (5.08) (-7.82) (10.29)GDP -0.4038 0.0005 0.0008 -0.0004 -0.0133

(-13.71) (0.94) (2.43) (-1.08) (-17.75)MCAP 0.0058 0.0021 -0.0009 0.0030 -0.0104

(0.19) (4.73) (-3.44) (10.56) (-16.65)Lambda -0.0144 -0.0107 -0.0034 0.0342

(-7.03) (-8.81) (-2.56) (12.39)X 2 11,779.6 4,562.2 9,052.5 12,855.4N 30,245 30,247 30,247 30,247

48

Table 9The Effect of Cross-Listing on Foreign Institutional Ownership

This table presents the impact on the level of institutional ownership of cross-listing in an U.S. exchange by non-U.S. firms. Panel A compares the level ofinstitutional ownership of non-US firms that are cross-listed in an U.S. exchange versus non-cross-listed firms. Figures are calculated for December 2000 andDecember 2004 and represent the average and median percentage of firms’ total stock market capitalization that is held by all foreign institutions, U.S. institutions,and non-U.S. foreign institutions. Panel B presents event study evidence on the change in median foreign institutional ownership with breakdown by U.S. andnon-U.S. institutions for firms that cross-listed in an U.S. exchange in our sample period from 2000 to 2004. Figures are percentages of total stock marketcapitalization of the event firms.

Panel A: Foreign Institutional Ownership of Cross-Listed versus Non-Cross-Listed Firms (%)Type of Number of All Institutions US Institutions Non-US Institutions

Date Firm Firms Mean Median Mean Median Mean MedianDec-2000 Cross-listed 329 8.61 6.47 5.64 3.59 3.00 2.00

Non-cross-listed 12,886 1.74 0.04 0.96 0.00 0.80 0.00Dec-2004 Cross-listed 419 10.61 8.73 5.76 4.02 4.8 3.60

Non-cross-listed 13,042 2.35 0.20 1.11 0.06 1.20 0.00

Panel B: Change in Median Foreign Institutional Ownership Around Cross-Listing (%)Local Shares ADR Shares Local and ADR Shares

Quarters Number of All US Non-US All US Non-US All US Non-USFirms Institutions Institutions Institutions Institutions Institutions Institutions Institutions Institutions Institutions

-4 101 0.12 0.09 0.00 0.00 0.00 0.00 0.21 0.16 0.00-3 101 0.39 0.15 0.09 0.00 0.00 0.00 1.37 0.30 0.19-2 101 0.67 0.11 0.08 0.00 0.00 0.00 1.22 0.43 0.45-1 101 0.75 0.18 0.12 0.00 0.00 0.00 1.75 0.47 0.270 101 2.92 0.77 0.76 0.03 0.01 0.00 3.97 1.56 1.141 101 3.56 1.19 1.57 0.06 0.04 0.00 5.28 2.11 2.032 100 4.08 1.15 1.97 0.05 0.04 0.00 5.46 2.37 3.053 95 3.64 1.12 2.04 0.05 0.02 0.00 5.32 2.18 2.414 92 4.74 1.44 2.23 0.05 0.02 0.00 6.70 2.53 2.605 88 4.41 1.77 2.36 0.06 0.02 0.00 6.60 2.77 2.626 83 5.18 1.91 2.54 0.04 0.01 0.00 7.74 3.10 3.307 80 6.26 2.07 2.80 0.08 0.03 0.00 7.81 2.97 3.698 78 5.88 2.28 2.86 0.11 0.04 0.00 7.40 3.04 3.40

49

Table 10Firm Valuation and Foreign and Domestic Institutional Ownership

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regression for non-US firmsvaluation measured by Tobin’s Q. The firm-level regressors include foreign institutional ownership (PF ) with break-down by U.S. and non-U.S. institutions, and domestic institutional onwership (PD), equity capitalization (SIZE), in-vestment opportunities (INV OP ), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), and global in-dustry Tobin’s Q (GLOBAL_Q). The country-level regressors include legal regime index (LEGAL), common law dummyvariable (COMMON), disclosure index (DISC), average geographic distance (DISTANCE), English language dummy(ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). Refer to Table B.1 of Appendix B forvariable definitions. The sample period is from 2000 to 2004. Robust t-statistics are in parentheses. Coefficients significantat the 5% level are in boldface.

Foreign Foreign Foreign DomesticVariable Ownership Ownership Ownership Ownership

All Inst. US Inst. Non-US Inst.Constant -0.1087 -0.0900 -0.1507 0.0343

(-0.45) (-0.37) (-0.62) (0.14)PF 0.6010 0.1857 1.2948

(5.18) (0.94) (7.36)PD -0.1595

(-2.33)SIZE 0.1002 0.1052 0.0997 0.1067

(33.30) (36.37) (33.67) (37.71)INV OP 0.2691 0.2703 0.2679 0.2703

(10.43) (10.45) (10.41) (10.44)LEV -0.0929 -0.0921 -0.0912 -0.0914

(-3.64) (-3.60) (-3.58) (-3.58)CASH 1.1354 1.1463 1.1363 1.1499

(17.65) (17.77) (17.70) (17.84)ADR -0.0814 -0.0646 -0.0761 -0.0626

(-2.54) (-2.02) (-2.39) (-1.99)GLOBAL_Q 0.6601 0.6635 0.6578 0.6644

(22.35) (22.52) (22.23) (22.53)LEGAL -0.0049 -0.0051 -0.0046 -0.0050

(-7.79) (-8.29) (-7.41) (-8.01)COMMON 0.1643 0.1642 0.1672 0.1671

(12.49) (12.45) (12.72) (12.63)DISC 0.1503 0.1568 0.1466 0.1606

(11.17) (11.68) (10.87) (11.88)DISTANCE -0.1652 -0.1763 -0.1585 -0.1943

(-7.04) (-7.52) (-6.75) (-7.95)ENGLISH 0.0961 0.0944 0.1022 0.0991

(5.45) (5.32) (5.82) (5.53)GDP 0.0000 0.0000 0.0000 0.0000

(-3.81) (-3.96) (-3.72) (-4.07)MCAP -0.0419 -0.0409 -0.0439 -0.0436

(-4.17) (-4.06) (-4.36) (-4.28)R2 0.2181 0.2169 0.2192 0.2170N 27890 27890 27890 27890

50

Table 11Firm Valuation and Foreign and Domestic Institutional Ownership:

Three-Stage Least Squares Regression

This table reports estimates of coefficients of the annual time-series cross-sectional firm-level regressions for non-US firmsvaluation measured by Tobin’s Q, and alternatively foreign institutional ownership (PF ) and domestic institutional onwer-ship (PD). The system of equations is estimated using three-stage least squares. The firm-level regressors include equitycapitalization (SIZE), book-to-market equity ratio (BM) investment opportunities (INV OP ), stock return (RET ), turnover(TURN), dividend yield (DY ), return-on-equity (ROE), idiosyncratic variance (SIGMA), MSCI index membership dummy(MSCI), leverage (LEV ), cash holdings (CASH), ADR listed dummy (ADR), closely held shares (CLOSE), and globalindustry Tobin Q (GLOBAL_Q). The country-level regressors include legal regime index (LEGAL), common law dummyvariable (COMMON), disclosure index (DISC), average geographic distance (DISTANCE), English language dummy(ENGLISH), GDP per capita (GDP ), and market capitalization to GDP (MCAP ). The sample period is from 2000 to2004. Robust t-statistics are in parentheses. Coefficients significant at the 5% level are in boldface.

Foreign DomesticInstitutions Institutions

Variable Ownership Valuation Ownership ValuationEquation Equation Equation Equation

Constant 0.0520 -0.1627 0.8449 1.5308(3.80) (-0.78) (46.61) (4.55)

PF 2.3647(5.73)

PD -2.0287(-6.16)

SIZE 0.0064 0.0837 0.0053 0.1136(29.81) (17.72) (18.62) (43.24)

BM -0.0051 0.0054(-13.26) (10.57)

INV OP 0.0050 0.2623 0.0021 0.2679(5.01) (15.04) (1.63) (15.36)

RET 0.0040 -0.0070(6.97) (-9.24)

TURN 0.0005 0.0023(1.68) (6.46)

DY -0.0005 0.0012(-4.26) (7.10)

ROE 0.0000 0.0001(3.32) (4.86)

SIGMA 0.0050 0.0035(3.80) (2.01)

MSCI 0.0209 -0.0135(21.96) (-10.69)

LEV -0.0072 -0.0954 0.0029 -0.0862(-4.24) (-3.76) (1.29) (-3.39)

CASH 0.0107 1.1089 0.0087 1.1574(4.16) (27.46) (2.56) (29.31)

ADR 0.0292 -0.1443 -0.0158 -0.0900(19.34) (-5.37) (-7.90) (-3.88)

CLOSE -0.0294 -0.0419(-21.98) (-23.60)

GLOBAL_Q 0.6473 0.6641(38.54) (39.86)

LEGAL -0.0006 -0.0040 0.0011 -0.0028(-15.12) (-6.13) (20.59) (-3.88)

COMMON -0.0015 0.1636 0.0132 0.1900(-1.38) (9.88) (9.24) (10.94)

DISC 0.0099 0.1302 0.0299 0.2002(10.10) (9.46) (23.01) (13.86)

DISTANCE -0.0149 -0.1299 -0.1059 -0.3937(-11.35) (-5.98) (-61.01) (-9.76)

ENGLISH -0.0015 0.0988 0.0156 0.1454(-1.34) (5.70) (10.22) (7.54)

GDP -0.0002 0.0000 -0.0116 0.0000(-0.34) (-3.37) (-16.03) (-5.71)

MCAP 0.0027 -0.0451 -0.0118 -0.0686(5.86) (-6.51) (-19.01) (-7.87)

R2 0.2553 0.2074 0.2968 0.1961N 27890 27890 27890 27890

51

Appendix A. FactSet/LionShares Institutional Ownership Database

Table A.1Institutional Holdings Data by Country and Year

This table contains the d istribution of FactSet/L ionShares institutional ownersh ip data by orig in country of institutions. M arket value of sto ck p ositions (in m illions of US$), number of institutions, and numberof indiv idual funds for each of the 27 orig in countries at the end of each year from 2000 to 2004 is shown. The column “5 Largest Institutions” lists the 5 largest institutional m anagers by equ ity assets held inDecember 2004. Column “3 Largest Funds” lists the 3 ind iv idual funds w ith the largest market value of assets under managem ent in December 2004. Institutions and funds names are abbrev iated.

Dec-2000 Dec-2001 Dec-2002 Dec-2003 Dec-2004 5 Largest Institutions 3 Largest FundsUS United States Total equity assets 3,925,349 3,437,354 2,835,326 3,823,488 4,720,429 1: F idelity (548 bil) 1: CREF Stock (109.2 bil)

Nr of institutions 1,095 1,158 1,145 1,128 1,110 2: Capita l R&M (524 bil) 2: Vanguard 500 Index Fund (106.2 b il)Nr of funds 5,630 6,066 5,933 5,787 5,751 3: Vanguard (306 bil) 3: American Funds G rowth Fund (76.6 bil)

4 : Wellington (163 b il)5 : T IAA-CREF (152 bil)

UK United K ingdom Total equity assets 266,663 354,208 360,307 514,100 536,832 1: JPMorgan Flem ing (41 bil) 1: INVESCO Perp etual UK -H igh Inc (6.3 bil)Nr of institutions 277 448 460 492 344 2: Schroder (38 b il) 2: Legal & General UK Index Trust (4 .9 b il)Nr of funds 734 1,325 1,535 1,624 1,205 3: F idelity Intl (34 b il) 3: Foreign & Colonia l Investm ent Trust (4 .1 bil)

4 : BG I (34 b il)5 : INVESCO (25 bil)

DE Germany Total equity assets 115,515 223,521 231,905 284,564 274,931 1: Deutche DWS (41 bil) 1: DWS Vermoegensbildungsfonds I (7 .5 bil)Nr of institutions 133 308 390 340 222 2: Deka (36 bil) 2: AriDeka (6.2 bil)Nr of funds 492 2,524 4,229 3,904 3,146 3: Deutscher Inv Trust (19 b il) 3: DekaFonds (4.6 b il)

4 : D resdnerbank (17 bil)5 : Com invest (15 bil)

CA Canada Total equity assets 76,948 175,325 172,222 255,736 247,199 1: CDP (26 bil) 1: Caisse Depot et P lacem ent Quebec (25.9 bil)Nr of institutions 30 205 242 246 172 2: CPP Invt Board (25 b il) 2: Canada Pension Plan (25.4 bil)Nr of funds 134 1,649 1,706 1,740 1,257 3: A IM Trimark (24 bil) 3: Ontario Teachers Pension Plan (12.8 b il)

4 : RBC (16 bil)5 : TD (13 bil)

FR France Total equity assets 25,297 52,089 97,984 204,755 150,992 1: IX IS (29 bil) 1: BNP Paribas Actions Euroland (4.6 b il)Nr of institutions 53 101 166 197 107 2: BNP Paribas (21 bil) 2: Ecureuil Dynam ic (3.1 bil)Nr of funds 66 229 691 948 799 3: AXA (11 bil) 3: Ecureuil Investissem ents (3 bil)

4 : Sogéposte (10 bil)5 : So c iété Générale (10 bil)

SE Sweden Total equity assets 17,701 50,333 61,450 109,403 147,123 1: Robur (24 b il) 1: A lecta Pension (16.1 bil)Nr of institutions 16 42 42 60 48 2: A lecta (16 bil) 2: Forsta AP Fonden (12 bil)Nr of funds 122 343 396 404 381 3: SEB (14 b il) 3: Skandia L iv (10.1 bil)

4 : Första AP (12 bil)5 : Nordea (10 b il)

NO Norway Total equity assets 1 ,441 30,893 38,888 70,834 94,257 1: Norges Bank (67 b il) 1: Norges Bank Staten Petroleum Fund (66.6 bil)Nr of institutions 7 26 28 30 28 2: Folketrygdfondet (7 bil) 2: Folketrygdfondet Pension Fund (6.6 b il)Nr of funds 24 147 159 179 172 3: Storebrand (5 b il) 3: V ita l Forsikring ASA (3 bil)

4 : V ita l Forsikring (3 bil)5 : DnB (3 bil)

IT Ita ly Total equity assets 16,420 56,116 52,887 77,546 82,541 1: Nextra (17 b il) 1: NEXTRA Azioni Europa (3 bil)Nr of institutions 23 54 87 100 50 2: San Paolo IM I (6 bil) 2: P ioneer Azionario Europa (1.7 bil)Nr of funds 100 462 641 657 599 3: Arca SGR (6 bil) 3: Sanpaolo Azion i Ita lia (1 .6 bil)

4 : F ineco (5 b il)5 : Azimut (5 b il)

CH Switzerland Total equity assets 52,269 73,588 71,769 96,756 81,052 1: UBS G lobal (31 bil) 1: UBS Equity Fund - Sw itzerland (2.6 b il)Nr of institutions 49 102 137 165 119 2: Capita l Intl (10 b il) 2: UBS 100 Index-Fund Sw itzerland (2.3 bil)Nr of funds 108 168 205 251 165 3: C redit Su isse (7 bil) 3: XMTCH on SM I (2.2 b il)

4 : P ictet Funds (6 bil)5 : Ju lius Baer (5 bil)

JP Japan Total equity assets 14,739 13,164 14,903 67,821 73,191 1: F idelity JP (20 bil) 1: F idelity JP Growth Open Mothers (6 bil)Nr of institutions 40 66 76 171 147 2: Nomura (11 b il) 2: Nomura Japanese Strategy Mothers (3 .8 bil)Nr of funds 11 311 412 3: JPMorgan Flem ing (5 bil) 3: F idelity Japan Open Fund (3.3 bil)

4 : Daiwa (4 b il)5 : Schroders Tosh ikomon (3 bil)

52

Table A.1: continuedDec-2000 Dec-2001 Dec-2002 Dec-2003 Dec-2004 5 Largest Institutions 3 Largest Funds

NL Netherlands Total equity assets 32,929 34,493 46,346 66,789 68,386 1: ING (19 bil) 1 : ING G lobal Equity Fonds (7.9 bil)N r of institutions 32 38 42 48 34 2: ABN AMRO (19 bil) 2 : Rob eco NV (7.3 bil)N r of funds 73 122 182 201 178 3: Robeco (14 b il) 3 : ING Europa Fonds (3.4 bil)

4 : Delta LLoyd (3 bil)5 : Fortis (3 bil)

ES Spain Total equity assets 3,207 21,532 21,149 33,001 40,213 1: BSCH (6 bil) 1 : Foncaixa Bolsa Euro, FI (1 bil)N r of institutions 22 173 279 251 214 2: BBVA (5 bil) 2 : BBVA Bolsa Europa, FI (0 .7 bil)N r of funds 94 1,372 2,981 3,367 3,340 3: Invercaixa (2 b il) 3 : Santander Central H isp Euroac, FI (0.6 bil)

4 : Urquijo (2 b il)5 : Gesbankinter (2 b il)

BE Belgium Total equity assets 24,872 30,229 26,555 38,763 39,484 1: Dexia (13 bil) 1 : Star Fund (2.3 bil)N r of institutions 22 39 35 43 37 2: KBC (11 b il) 2 : Fortis B Pension Fund (1.8 bil)N r of funds 187 319 341 362 356 3: ING (5 bil) 3 : Dexia Fullinvest - M edium (1.6 bil)

4 : Fortis (3 bil)5 : Banque Degro of (2 b il)

HK Hong Kong Total equity assets 16,344 15,185 16,701 31,524 36,004 1: Templeton (7 b il) 1 : Tracker Fund of Hong Kong (3.9 bil)N r of institutions 41 64 54 56 52 2: JF (6 bil) 2 : JF Pacifi c Securities Fund (0.5 bil)N r of funds 1 6 9 27 3: F idelity HKG 3: JF Japan (Yen) Fund (0.4 b il)

4 : State Street (4 bil)5 : Schroder HKG (2 bil)

DK Denmark Total equity assets 4,636 10,099 17,752 34,965 35,351 1: ATP Arb ejdsmarkedets T illægs(6 b il) 1 : ATP Pension Fund (5.6 bil)N r of institutions 11 26 36 41 26 2: Nordea (5 b il) 2 : Dan ica Pension (2.6 bil)N r of funds 27 145 219 239 227 3: Danske Invest (5 b il) 3 : LD Pension - Lonmodtagernes Dyrtids (2 .4 b il)

4 : PKA (4 bil)5 : Danica Pension (3 bil)

IE Ireland Total equity assets 8,806 22,629 20,084 29,355 32,768 1: P ioneer (17 bil) 1 : National Pensions Reserve Fund Com (12 bil)N r of institutions 11 17 16 17 11 2: F ideuram (14 b il) 2 : DekaTeam GlobalSelect (3.7 bil)N r of funds 164 327 555 602 523 3: AGF (1 bil) 3 : ETF iShares DJ Euro STOXX 50 (2.7 bil)

4 : Montgom ery Opp enheim (1 bil)5 : Bank of Ireland (0.3 bil)

SG Singap ore Total equity assets 6,779 9,135 10,425 19,066 25,816 1: Ab erdeen (6 b il) 1 : A IG - Acorns of A sia Balanced Fund (0.3 b il)N r of institutions 36 55 53 64 50 2: Templeton (3 b il) 2 : StreetTRACKS STI (0.3 bil)N r of funds 1 81 67 3: Schroder SG (2 bil) 3 : Schroder Asian Growth Fund (0.2 bil)

4 : Deutsche Asset Mngt Asia (2 bil)5 : P ioneer Singap ore (1 bil)

LU Luxembourg Total equity assets 1,419 11,697 10,360 19,023 22,677 1: SanPaolo IM I Lux (7 b il) 1 : F idelity SICAV European Growth (18.2 bil)N r of institutions 8 48 61 77 46 2: Nordea Bank Lux (3 bil) 2 : Capita l Intl SICAV G lobal Equ ity (6.1 b il)N r of funds 758 2,306 2,831 3,167 2,343 3: Kredietrust (2 bil) 3 : Franklin -Templeton Growth Fund (5.8 bil)

4 : DWS Lux (2 b il)5 : Banque de Luxembourg (2 bil)

FI F in land Total equity assets 710 5,134 9,994 22,298 22,074 1: Varma-Sampo (6 bil) 1 : Varma Sampo Pension Fund (5.5 bil)N r of institutions 6 21 28 41 29 2: Ilmarinen Mutual (4 bil) 2 : Ilm arinen Mutual Pension Insurance (4 b il)N r of funds 35 151 175 192 192 3: Opsto ck (2 bil) 3 : The State Pension Fund (1.8 bil)

4 : State Pension Fund (2 b il)5 : Mandatum Rahastoythtio (1 b il)

ZA South A frica Total equity assets 160 259 4,807 8,187 14,116 1: O ld Mutual A sset Managers (3 bil) 1 : A llan G ray - Equity Fund (1.2 bil)N r of institutions 1 4 43 43 21 2: A llan G ray Unit Trust (2 bil) 2 : Nedbank Rainmaker Fund (0.9 bil)N r of funds 188 168 147 3: Investec (2 b il) 3 : A llan G ray - Balanced Fund (0.8 bil)

4 : Stanlib (1 b il)5 : Polaris Cap ita l ZA (1 bil)

AU Australia Total equity assets 1,026 1,489 3,291 5,745 7,271 1: UBS AU (3 bil) 1 : UBS AU Share Fund (2.6 bil)N r of institutions 7 8 14 15 19 2: BT Funds AU (1 b il) 2 : JBWere Emerging Leaders Pooled(0.5 bil)N r of funds 5 7 68 3: Goldman Sachs JBWere (1 b il) 3 : JBWere G lobal Small Companies (0 .4 bil)

4 : Deutsche AU (0.5 bil)5 : Credit Suisse AU (0.4 b il)

AT Austria Total equity assets 2,331 3,278 3,957 5,316 6,390 1: Cap ital Invest (1 bil) 1 : Raiff eisen - Europa (0.7 b il)N r of institutions 21 35 45 47 42 2: Raiff eisen (1 bil) 2 : Raiff eisen - O steuropa (0.5 bil)N r of funds 72 163 216 256 215 3: Volksbanken (1 bil) 3 : Raiff eisen - US (0.4 bil)

4 : Erste Sparinvest (1 bil)5 : Gutmann (0.4 bil)

53

Table A.1: continuedDec-2000 Dec-2001 Dec-2002 Dec-2003 Dec-2004 5 Largest Institutions 3 Largest Funds

IN Ind ia Total equity assets 226 119 123 3,884 5,557 1: UTI (2 bil) 1 : Frank lin India B lue Chip Fund (0.4 bil)Nr of institutions 2 3 3 31 27 2: Franklin Templeton IN (1 bil) 2 : UTI - MasterShare Unit Schem e (0.3 b il)Nr of funds 174 191 3: HSBC IN (0.4 bil) 3 : UTI - Unit L inked Insurance P lan (0.3 b il)

4 : P rudentia l IC IC I (0.3 bil)5 : B irla Sun Life (0 .3 b il)

LI L iechtenstein Total equity assets 901 2,363 2,929 1: LGT (2 bil) 1 : C lassic G lobal Equity Funds (0.9 b il)Nr of institutions 10 12 13 2: LLB (1 bil) 2 : LGT Equity Fund G lobal Sector (USD) (0.5 bil)Nr of funds 69 91 87 3: CATAM (0.1 bil) 3 : LGT Equity Fund Cont Europ e (EUR) (0.4 bil)

4 : P rincipal Vermoegensverwalt (0.1 bil)5 : Serica Fondsle itung (0.1 bil)

PT Portugal Total equity assets 881 834 1,145 2,180 2,741 1: CAIXAGEST (0.5 bil) 1 : Tranquilidade PPR (0.2 bil)Nr of institutions 9 8 19 45 34 2: BPI Fundos (0.4 bil) 2 : BPI G lobal (0 .2 b il)Nr of funds 21 29 103 158 180 3: Santander (0 .4 bil) 3 : AF PPA (0.2 b il)

4 : M illennium BCP (0.3 bil)5 : Tranqu ilidade V ida (0.2 bil)

GR Greece Total equity assets 324 1,060 1,985 1: EFG Eurobank (1 bil) 1 : Hellenic Investm ent (0.5 bil)Nr of institutions 23 19 18 2: Hellen ic Investment (0.5 b il) 2 : Eurobank Formula II Fore ign Fund (0.3 bil)Nr of funds 54 59 60 3: P roton (0.1 b il) 3 : Eurobank C lick Intern Balanced Fund (0.2 b il)

4 : A lpha Asset Mgt (0.1 bil)5 : A lpha Trust (0 .1 bil)

PL Poland Total equity assets 1 ,101 1,125 1: P ioneer Pekao (0.5 bil) 1 : P ioneer Zrownowazony FIO (0.5 b il)Nr of institutions 16 11 2: DWS PL (0.2 bil) 2 : CU FIO Polsk ich Akcji (0.1 bil)Nr of funds 49 23 3: Commercia l Union PL (0.1 bil) 3 : Skarbiec-Akcja (0.1 bil)

4 : Skarbiec (0.1 bil)5 : M illennium (0.1 bil)

A ll Total equity assets 4 ,627,461 4,653,598 4,158,521 5,858,408 6,798,577Nr of institutions 1,952 3,049 3,534 3,795 3,031Nr of funds 8,841 17,848 23,432 24,987 22,111

54

Table A.2Cross-Country Institutional Investors Stock Holdings

This table provides the distribution of the market value of sto ck holdings by 27 orig in countries of institutions (in rows) and destination countries of sto cks (in columns) as of December 2004. An extra category“Other” groups all remain ing 21 countries that are mostly recip ient countries in the FactSet/L ionShares dataset. F igures are in billion US$, and values greater than US$1 b illion are in b oldface. Countries nam esare abbreviated (refer to Table A .1 for fu ll countries names).

Destination Country Sto ck MarketUS UK DE CA FR SE NO IT CH JP NL ES BE HK DK IE SG LU FI ZA AU AT IN LI PT GR PL Other Total

US 3,776 176 45 88 66 15 8 19 57 118 51 22 6 18 7 14 7 2 11 10 22 4 15 0.0 2 2 1 159 4,720UK 52 239 23 5 32 6 3 15 20 34 16 11 4 5 2 5 2 1 4 4 6 2 2 0.0 1 3 2 36 537DE 34 31 71 1 37 3 1 12 13 11 20 14 4 1 0.8 2 0.5 0.8 5 0.2 1 1 0.6 0.0 0.5 1 0.6 7 275CA 59 11 2 149 3 0.7 0.2 1 2 6 2 0.9 0.2 0.7 0.5 1 0.3 0.1 0.4 0.3 2 0.1 0.1 0.0 0.1 0.1 0.0 4 247FR 13 8 11 0.6 77 0.8 0.4 6 3 5 7 6 3 0.6 0.3 1 0.1 1 2 0.3 0.2 0.6 0.2 0.0 0.4 0.7 0.3 3 151SE 29 12 4 0.8 4 73 1 1 5 4 2 2 0.4 0.5 1 0.4 0.2 0.8 2 0.0 0.5 0.2 0.0 0.0 0.1 0.1 0.2 3 147NO 29 12 4 1 6 3 13 2 4 5 2 2 0.7 0.5 1 0.6 0.3 0.2 1 0.4 1 0.3 0.1 0.0 0.3 0.3 0.0 3 94IT 18 9 5 0.3 7 0.8 0.1 21 3 7 3 2 0.6 0.5 0.2 0.3 0.2 0.1 0.9 0.2 0.9 0.1 0.1 0.0 0.1 0.3 0.2 2 83CH 19 7 5 1 5 0.6 0.3 2 20 5 4 2 0.6 0.5 0.2 0.6 0.1 0.1 1.0 0.5 0.5 0.3 0.2 0.0 0.2 0.1 0.2 5 81JP 3 0.9 0.2 0.2 0.3 0.1 0.0 0.1 0.2 63 0.1 0.1 0.0 2 0.1 0.0 0.1 0.0 0.0 0.1 0.2 0.0 0.1 0.0 0.0 0.0 0.0 3 73NL 20 8 3 0.6 4 3 0.4 2 3 4 11 1 0.8 0.8 0.3 0.6 0.2 0.1 0.5 0.3 0.5 0.2 0.3 0.0 0.1 0.3 0.1 4 68ES 4 3 3 0.1 4 0.2 0.0 1 1 0.7 2 18 0.3 0.0 0.0 0.1 0.0 0.3 0.6 0.0 0.0 0.0 0.0 0.0 0.3 0.0 0.0 0.6 40BE 8 4 3 0.2 5 0.5 0.2 1 2 1 2 2 7 0.2 0.1 0.4 0.0 0.2 0.7 0.1 0.1 0.1 0.0 0.0 0.1 0.2 0.0 0.7 39HK 0 2 0 0.0 0.0 0.0 0.0 0.0 0.0 2 0.0 0.0 0.1 10 0.0 0.0 2 0.0 0.0 0.3 1 0.2 2 0.0 0.0 0.1 0.2 15 36DK 6 3 1 0.2 1 1 0.3 0.5 1 2 0.6 0.7 0.2 0.6 13 0.1 0.1 0.0 0.3 0.0 0.2 0.1 0.3 0.0 0.0 0.0 0.2 3 35IE 6 5 2 0.0 4 0.3 0.1 5 2 2 0.9 1 0.4 0.5 0.1 0.7 0.1 0.0 0.1 0.1 0.6 0.0 0.1 0.0 0.0 0.0 0.1 2 33SG 0.5 0.4 0.1 0.0 0.2 0.0 0.0 0.1 0.1 3 0.1 0.1 0.0 4 0.0 0.0 2 0.0 0.0 0.0 2 0.0 1 0.0 0.0 0.0 0.1 11 26LU 5 3 2 0.2 2 0.6 0.1 1 1 2 1 0.6 0.3 0.4 0.2 0.3 0.1 0.3 0.5 0.1 0.3 0.1 0.1 0.0 0.0 0.1 0.0 1 23FI 1 2 1 0.0 1 2 0.3 0.4 0.8 0.2 0.8 0.4 0.1 0.0 0.2 0.1 0.0 0.0 10 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.1 0.6 22ZA 0.5 1 0.0 0.1 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 11 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 14AU 0.6 0.2 0.0 0.3 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 0.0 0.0 5 0.0 0.0 0.0 0.0 0.0 0.0 0.5 7AT 2 0.6 0.4 0.0 0.4 0.0 0.0 0.1 0.3 0.4 0.3 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.7 0.0 0.0 0.0 0.0 0.2 1.0 6IN 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 6 0.0 0.0 0.0 0.0 0.0 6LI 0.8 0.2 0.2 0.0 0.2 0.1 0.0 0.1 0.5 0.4 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 3PT 0.3 0.1 0.2 0.0 0.2 0.0 0.0 0.1 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1 0.0 0.0 0.0 3GR 0.5 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.8 0.0 0.1 2PL 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1 0.0 1Other 0.9 2 0.3 0.1 1 0.4 0.0 0.4 0.9 3.3 0.4 0.2 0.0 0.2 0.1 0.0 0.3 0.0 0.1 1 0.2 0.0 0.1 0.0 0.0 0.0 0.1 4 16Total 4 ,089 539 185 249 261 112 29 91 140 281 128 86 28 47 27 28 16 7 42 29 45 10 28 0 7 9 6 267 6,789

55

Table A.3Institutional Investors Stock Holdings by Country

Panel A presents the market value of stock holdings by institutional investors in each destination country (corresponding to columns of Table A.2). Market value (MV) of stocks held byall institutions, domestic institutions, and foreign institutions with breakdown by non-U.S. and U.S. institutions is shown. Panel B presents the fraction of each country’s stock markettotal capitalization that is held by all institutions, domestic institutions, and foreign institutions with breakdown by non-U.S. and U.S. institutions. Panel C presents the fraction of eachcountry’s stock market float (i.e. market value of stock that is not closely held and is investable by outside shareholders) that is held by all institutions, domestic institutions, and foreigninstitutions with breakdown by non-U.S. and U.S. institutions. Panel D presents the domestic market portfolio weight, domestic holdings by domestic institutions, and domestic bias foreach origin country of institution. Domestic bias is calculated as the logarithm of the ratio of the domestic market weight by the domestic holdings of domestic institutions. Countriesnames are abbreviated (refer to Table A.1 for full countries names).

Destination Country Stock Market US UK DE CA FR SE NO IT CH JP NL ES BE HK DKPanel A: Market Value of Stocks Held by Institutions

Number. of stocks held 7,028 2,145 833 1,791 674 327 188 322 270 3,536 197 189 223 772 164MV held by all institutions (US$ billions) 4,089 539 185 249 261 112 29 91 140 281 128 86 28 47 27MV held by domestic institutions (US$ billions) 3,776 239 71 149 77 73 13 21 20 63 11 18 7 10 13MV held by foreign institutions (US$ billions) 313 301 114 101 185 39 16 70 120 218 116 68 21 36 15MV held by non-U.S. foreign institutions (US$ billions) 313 125 69 12 119 23 8 51 63 101 66 46 15 18 8MV held by U.S. foreign institutions (US$ billions) 0 176 45 88 66 15 8 19 57 118 51 22 6 18 7

Panel B: Fraction of Stock Market Total Capitalization Held by InstitutionsMarket capitalization (US$ billions) 14,381 3,035 1,153 1,048 1,548 339 143 756 835 3,751 626 637 307 600 131% held by all institutions 28.4 17.8 16.0 23.8 16.9 32.9 20.5 12.0 16.8 7.5 20.4 13.5 9.3 7.8 20.9% held by domestic institutions 26.3 7.9 6.2 14.2 5.0 21.5 9.1 2.8 2.4 1.7 1.8 2.9 2.4 1.7 9.8% held by foreign institutions 2.2 9.9 9.8 9.6 11.9 11.4 11.4 9.3 14.4 5.8 18.6 10.6 6.8 6.0 11.1% held by non-U.S. foreign institutions 2.2 4.1 6.0 1.2 7.7 6.9 5.5 6.8 7.5 2.7 10.5 7.2 5.0 3.0 5.8% held by U.S. foreign institutions 0.0 5.8 3.9 8.4 4.2 4.6 5.9 2.5 6.8 3.1 8.1 3.4 1.9 3.0 5.3

Panel C: Fraction of Stock Market Float Held by Institutions% of closely held shares 10.3 11.1 40.7 19.4 31.4 21.1 54.5 34.6 26.0 34.1 23.1 40.6 40.7 61.5 37.4Investable market float (US$ billions) 12,898 2,698 683 845 1,062 268 65 495 618 2,474 482 379 182 231 82% held by all institutions 31.7 20.2 27.0 29.5 24.6 41.7 45.1 18.4 22.7 11.4 26.5 22.7 15.6 20.1 33.4% held by domestic institutions 29.3 8.8 10.4 17.6 7.2 27.2 20.0 4.2 3.2 2.5 2.3 4.8 4.1 4.5 15.7% held by foreign institutions 2.4 11.1 16.6 11.9 17.4 14.5 25.0 14.2 19.4 8.8 24.2 17.9 11.5 15.7 17.7% held by non-U.S. foreign institutions 2.4 4.6 10.1 1.5 11.2 8.7 12.1 10.4 10.2 4.1 13.7 12.1 8.4 7.8 9.3% held by U.S. foreign institutions 0.0 6.5 6.5 11.0 6.2 5.8 13.0 3.8 9.2 4.8 10.5 5.8 3.2 7.8 8.4

Origin Country of Institution US UK DE CA FR SE NO IT CH JP NL ES BE HK DKPanel D: Domestic Holdings and Bias by Institutions

Domestic market weight (%) 42.12 8.89 3.38 3.07 4.54 0.99 0.42 2.22 2.45 10.99 1.84 1.87 0.90 1.76 0.38Domestic holdings by domestic institutions (%) 80.0 44.5 25.9 60.2 50.7 49.5 13.8 25.2 24.7 85.5 16.3 45.3 18.9 28.8 36.3Domestic bias (%) 64.2 161.0 203.8 297.7 241.6 390.8 349.8 243.3 205.2 205.2 218.1 318.9 304.6 279.7 455.0

56

Table A.3: continuedDestination Country Stock Market IE SG LU FI ZA AU AT IN LI PT GR PL Other Total Non-US

Panel A: Market Value of Stocks Held by InstitutionsNumber of stocks held 77 341 57 155 258 692 108 565 2 56 233 154 4,145 25,502 18,474MV held by all institutions(US$ billions) 28 16 7 42 29 45 10 28 0 7 9 6 267 6,789 2,700MV held by domestic institutions (US$ billions) 1 2 0 10 11 5 1 6 0 1 1 1 4 4,605 829MV held by foreign institutions (US$ billions) 27 14 7 31 18 40 10 23 0 5 9 5 264 2,184 1,872MV held by non-U.S. foreign institutions (US$ billions) 13 7 5 20 8 18 6 8 0 3 6 4 105 1,240 927MV held by U.S. foreign institutions (US$ billions) 14 7 2 11 10 22 4 15 0 2 2 1 159 944 944

Panel B: Fraction of Stock Market Total Capitalization Held by InstitutionsMarket capitalization (US$ billions) 115 186 55 174 259 744 86 307 3 78 122 55 2,665 34,141 19,760% held by all institutions 24.2 8.8 13.1 23.9 11.3 6.1 12.1 9.3 4.5 8.6 7.6 11.8 10.0 19.9 13.7% held by domestic institutions 0.6 1.3 0.6 5.9 4.4 0.7 0.8 1.8 1.1 1.8 0.6 1.9 0.1 13.5 4.2% held by foreign institutions 23.6 7.5 12.5 18.0 6.8 5.4 11.3 7.5 3.4 6.8 7.0 10.0 9.9 6.4 9.5% held by non-U.S. foreign institutions 11.5 3.6 8.9 11.6 3.0 2.5 7.0 2.6 3.1 4.1 5.1 8.1 3.9 3.6 4.7% held by U.S. foreign institutions 12.1 3.8 3.7 6.4 3.8 2.9 4.3 4.9 0.3 2.7 1.8 1.9 60. 2.6 4.8

Panel C: Fraction of Stock Market Float Held by Institutions% of closely held shares 9.7 38.6 49.4 16.9 42.6 31.2 57.4 58.6 n.a. 38.0 44.1 55.0 n.a. 22.2 29.6Investable market float (US$ billions) 104 114 28 145 149 512 37 127 n.a. 48 68 25 n.a. 24,817 11,919% held by all institutions 26.8 14.3 26.0 28.8 19.6 8.8 28.5 22.4 n.a. 13.8 13.6 26.3 n.a. 27.4 22.7% held by domestic institutions 0.7 2.2 1.2 7.1 7.7 1.0 1.9 4.3 n.a. 2.9 1.2 4.2 n.a. 18.6 7.0% held by foreign institutions 26.2 12.2 24.7 21.7 11.9 7.8 26.5 18.1 n.a. 11.0 12.5 22.1 n.a. 8.8 15.7% held by non-U.S. foreign institutions 12.8 5.9 17.5 14.0 5.2 3.6 16.5 6.3 n.a. 6.6 9.2 17.9 n.a. 5.0 7.8% held by U.S. foreign institutions 13.4 6.3 7.2 7.7 6.7 4.2 10.1 11.8 n.a. 4.3 3.3 4.2 n.a. 3.8 7.9

Origin Country of Institution IE SG LU FI ZA AU AT IN LI PT GR PL Other Total Non-USPanel D: Domestic Holdings and Bias by Institutions

Domestic market weight (%) 0.34 0.55 0.16 0.51 0.76 2.18 0.25 0.90 0.01 0.23 0.36 0.16Domestic holdings by domestic institutions (%) 2.1 9.7 1.5 46.5 81.4 70.7 11.1 99.3 1.0 50.4 39.7 91.8Domestic bias (%) 184.4 287.4 225.2 451.1 467.4 347.9 377.9 470.3 487.2 539.9 470.6 635.2

57

Appendix B

Table B.1Variables Definition

Variable DefinitionPanel A: Firm-Level Control Variables

Market capitalization (log) SIZE Log annual market capitalization in US$ (WS item 02999)Book-to-market (log) BM Log of the book-to-market equity ratio (end-of-year market value of equity is from DS

and book value of equity is WS item 03501).Investment opportunities INV OP Two-year geometric average of annual growth rate in net sales in US$ (WS item 01001)Annual stock return RET Annual (end-of-year) geometric stock rate of return (DS item P)Turnover TURN Annual share volume (DS item VO) divided by adjusted shares outstanding (DS items NOSH/AF)Dividend yield DY Dividend yield (WS item 09404)Return-on-equity ROE Return-on-equity (WS item 08301)Idiosyncratic variance SIGMA Idiosyncratic variance estimated from the domestic market model.MSCI membership dummy MSCI MSCI member dummy, which equals one if a firm is a member of the MSCI All-country World IndexLeverage LEV Ratio of total debt (WS item 03255) to total assets (WS item 02999)Cash CASH Ratio of cash and short term investments (WS item 02001) to total assets (WS item 02999)ADR listed dummy ADR ADR dummy, which equals one if a firm is cross-listed on an US exchangeClosely held shares CLOSE Number of shares held by insiders as a proportion of the number of shares outstanding (WS item 08021)Foreign sales FXSALES International annual net sales (WS item 07101) as a proportion of net sales (WS 01001)Number of analysts ANALY STS Number of analysts covering a firm as reported by I/B/E/SCorporate governance ranking CGQ Overall corporate governance ranking by Institutional Shareholder Service (ISS)Tobin’s Q Q Sum of total assets (WS item 02999) plus market value of equity (WS item 02999) less

book value of equity WS item 03501) divided by total assetsGlobal industry Tobin’s Q GLOBAL_Q Median Tobin’s Q of firms in each two-digit SIC global industry

Panel B: Country-Level Control VariablesLegal regime quality index LEGAL Anti-director rights (shareholders rights) multiplied by the rule of law index (LLSV (1998))Common law dummy COMMON Legal origin dummy variable, which equals one if a country has a common law origin (LLSV (1998))Disclosure quality index DISC Accounting transparency index (Global Competitiveness Report)Average distance (log) DISTANCE Average bilateral distance in kilometers (log) between a country capital city and other capital citiesEnglish language dummy ENGLISH English language dummy variable, which equals one when a country’s official language is English (World Factbook)GDP per capita (log) GDP Annual log gross domestic product per capita in US$ (World Bank WDI)Market capitalization to GDP MCAP Annual ratio of stock market capitalization to gross domestic product in US$ (World Bank)

58